区域及全球尺度的NPP过程模型和NPP对全球变化的响应

植被净第一性生产力（NPP）不仅是表征植被活动和生态过程的关键参数,而且是判定生态系统碳汇和反映生态系统对全球变化响应的主要因子。当前,模型模拟成为大尺度NPP研究的主要手段,而在众多NPP估算模型中,过程模型逐渐趋于主导地位。虽然目前有关NPP的研究有很多,但还没有关注于大尺度上应用的过程模型及其模拟的NPP对全球变化的响应。因此本文主要侧重于 NPP 过程模型在区域及全球尺度上的应用,具体包含以下内容,①进一步将区域及全球尺度的NPP过程模型分为静态植被模型和动态植被模型。②阐明这些模型间存在的区别与联系。③归纳出NPP过程模型在区域及全球尺度上应用的3大挑战：时空尺度转换、多源数据的获取与融合以及模型模拟结果的验证与评价,并根据其解决方案总结出通用的模型应用框架。④从气候变化、大气成分变化和土地利用/土地覆盖变化3个方面探讨NPP对全球变化的响应机制,以期找到NPP变化的规律与模式。最后根据NPP模型的发展对未来区域及全球尺度的NPP过程模型进行展望,认为未来模型的综合性将更高,机理性也将更强,同时与全球变化研究结合得更加紧密,且基于多个已有模型的混合模型也是未来NPP模型发展的一个重要方向。此外,本文认为对NPP模拟结果的尺度效应研究也是未来NPP研究的热点之一。     

基于森林清查和遥感的城市森林净初级生产力估算

城市森林作为陆地生态系统的组成成分之一,研究其在全球碳循环中的地位和作用有很重要的意义.文章以上海城市森林为研究对象,开展基于基于森林清查数据和遥感技术的城市森林净初级生产力(NPP)估算研究.首先,根据选取上海市典型的森林植被类型,设置森林植被样方,测量反映植被生物学特性的特征参数,包括林龄、胸径、树高和叶面积指数(LAI)等,采用能反映林龄和蓄积量共同影响的生产力回归模型估算了样方NPP,建立了基于LAI的样方NPP回归模型;其次,利用一景相近时相的SPOT5影像,经进行几何纠正和辐射定标后,计算出能较好地反映植被特征和消除土壤背景影响的修正土壤调节植被指数(MSAVI),建立了基于MSAVI的区域森林LAI遥感估测模型;最后,根据建立的样方NPP回归模型以及区域LAI遥感估测模型,进行尺度化转换,估算出区域尺度上的上海城市森林净初级生产力.通过比较与前人运用传统方法研究估算的NPP,精度可达到89%,且本模型简单可行.因此本研究可为快速定量评估城市森林碳储量提供依据.     

基于生态过程模型和森林清查数据的森林生长量估算对比研究

利用遥感驱动的生态过程模型-Boreal Ecosystem Productivity Simulator （BEPS）、2001-2006年国家森林资源连续清查数据（一类清查-样地尺度）和2003-2009年森林资源规划设计调查数据（二类调查-区域尺度）,分别计算江西省吉安市的森林生态系统生长量,从不同空间尺度和森林类型对3种数据源估算的森林生长量进行了分析。结果表明,样点尺度上,BEPS模型模拟的森林生长量（4.18 Mg·hm^-2·a^-1）低于群落生长量（5.86 Mg·hm^-2·a^-1）,与乔木层生长量（4.29 Mg·hm^-2·a^-1）基本一致,模型模拟结果与两者的拟合R2分别为0.48和0.43。区域尺度上,BEPS模型模拟、二类调查数据计算的群落及乔木层生长量分别为4.65、4.36和3.34 Mg·hm^-2·a^-1,BEPS模型估算的吉安市各县森林总生长量与二类调查数据计算的群落、乔木层生长总量拟合R2分别达0.84和0.83。一类清查数据计算结果高于二类清查数据计算结果,BEPS模型模拟森林生长量分别与基于一类清查数据计算的乔木层生长量及二类调查数据群落生长量较为一致。从研究区两种主要森林类型来看,常绿阔叶林年平均生长量高于常绿针叶林,常绿针叶林与模型估算结果差异小于常绿阔叶林。最后利用模型估算了研究区2001-2010年平均生长量,为认识研究区的森林生长空间分布差异及更新森林生物量提供支持。     

中国农田作物植被碳储量研究进展

作物植被碳储量是全球陆地生态系统碳库的重要组成部分。中国农田作物植被碳储量的估算主要采用参数估算法、遥感资料反演法和环境参数模型法。通过对中国近几十年来全国和区域尺度作物植被碳储量的估算研究,获得了一些作物的经济系数、含碳率和作物收获部分水分系数等估算参数值,探讨了遥感反演和环境参数模型方法,并提出加强农田基本建设、改进农业生产技术与管理、调整作物结构和加强作物秸秆利用等固碳措施。目前对中国农田作物植被碳储量的估算仍存在较大的不确定性,获取的估算参数尚不充分,估算方法和模型有待完善,对作物植被碳储量变化的源/汇效应尚未取得统一认识。虽然在农田生态系统中土壤碳储量（密度）普遍大于作物植被碳储量（密度）,但作物植被碳储量仍然是一个数量可观、并有增加潜力和可能的碳库,其大小及秸秆利用情况直接影响着土壤碳库。因此,对农田作物植被碳储量应分时段和区域具体分析,才能认识其源/汇效应。今后应在以下几方面进一步加强作物植被碳储量的研究：进一步完善和改进估算方法;加强作物植被碳储量估算及固碳措施的区域个例研究,探索不同空间尺度作物植被碳储量的尺度转换;开展作物碳储量动态及固碳机理的综合研究。此外,还应就气候变化与作物植被碳储量的相互耦合关系进行探讨。     

畜禽养殖氨排放核算方法和模型比较

系统梳理了国内外氨排放核算方法体系及相关模型,比较和评价了基于物质流核算和基于阶段管理模型的两类模型方法的优缺点和适用范围,认为在地区范围基于总氨态氮的物质流核算方法得出的结果较基于总氮的核算方法得出的结果更准确,而基于阶段管理的氨排放估算方法则更适合养殖场尺度氨排放核算;基于目前我国氨排放研究重点关注区域宏观核算和对微观管理指导不足的客观现实,提出了适合我国国情的综合阶段管理模型和区域统计模型的自下而上畜禽养殖氨排放核算框架新思路;指出未来氨排放核算研究重点包括阶段管理模型的精度提升、区域统计量的收集和数据准确度的提升、规模化畜禽养殖管理模式基础信息收集和粪污处理技术优化等方面,以期为我国畜禽养殖分区管理和精准治污提供理论指导和现实依据。     

不同尺度中国大陆灵长目物种丰富度的地理格局及其与环境因子和人类活动的关系

物种丰富度的分布格局及其成因有多种假说,其中生态假说中能量假说、生境异质性假说和气候假说目前被广泛接受.本文通过代表不同假说的26个环境变量,同时也利用人口密度、农田牧场面积表征人类活动强度,分别在100 km×100 km、200 km×200 km和400 km×400 km尺度上,基于特征值的空域滤波模型的方法分析中国大陆灵长类物种丰富度与环境因子和人类活动之间的关系.结果表明,在所有分析的空间尺度上,中国大陆灵长类物种丰富度呈现纬度梯度格局,即由南向北逐渐递减.其中,华南区的滇西南山地省和滇南边地省是物种最为丰富的区域,东北区、华北区、蒙新区和青藏区大部分地区基本上没有分布.在不同空间尺度上,虽然影响中国大陆灵长类物种丰富度大尺度格局的主要因素不相一致,但环境能量假说(以潜在蒸发散表示)和气候假说(以年均温度表示)相互作用,共同影响中国大陆灵长类物种丰富度大尺度地理分布格局.当表征人类活动相关的指标和环境因子一起分析时,结果表明人类活动强度对灵长类物种丰富度地理格局有影响,这对加强灵长类物种保护有参考意义.     

城市垃圾能量估算方法探讨

本文根据Ｄｕｌｏｎｇ公式的计算结果，建立了根据城市垃圾组成的重量百分比估算城市垃圾能量的经验公式，并对它进行了检验。估算结果与Ｄｕｌｏｎｇ公式的计算结果进行相关分析，相关系数在０．９８以上，该经验公式具有较好的推广价值，用此公式对我国部分城市垃圾的能量进行了估算。     

不同制图比例尺土壤数据库对旱地磷储量估算的影响

陆地生态系统中的磷元素在土壤肥力保持和生态环境保护方面起着重要的作用,但以往国家或区域尺度磷储量估算并没有考虑不同尺度土壤数据库所造成的差异。文章以江苏北部29个县（市）390多万hm2旱地为例,分析了17 000多个图斑和963个剖面组成、能详尽反映土壤属性空间异质性的1∶50 000数据库与目前国内同类研究使用最多的1∶1 000 000和1∶4 000 000土壤数据库对磷储量估算的影响。结果表明,不同制图尺度土壤数据库估算的全磷密度和储量差异很大,1∶50 000土壤数据库下的全磷密度和储量分别为1.34 kg.m-3和10.52 Tg,而1∶1 000 000和1∶4 000 0002个土壤数据库下磷密度和储量分别为0.79 kg.m-3和6.02 Tg、0.77 kg.m-3和6.26 Tg,远小于1∶50 000土壤数据库的全磷密度和储量。从不同土壤类型看,褐土受制图比例尺影响最大,1∶1 000 000和1∶4 000 000土壤数据库下与1∶50 000土壤数据库全磷密度和储量相对偏差分别在80%~90%和7%~130%之间,面积最大的潮土在1∶1 000 000和1∶4 000 000土壤数据库下与1∶50 000全磷密度和储量相对偏差也分别达到38%~39%和21%~23%。从各个县（市）来看,1∶1 000 000和1∶4 000 000土壤数据库下与1∶50 000土壤数据全磷密度和储量相对偏差大多超过40%。这也说明使用不同制图尺度土壤数据库将对旱地磷储量和磷密度的估算结果造成很大的影响。因此,在今后的国家和区域尺度全磷密度和储量估算研究中使用更详细的土壤数据库是非常必要的。     

基于FLUXNET的CLM模型生态系统呼吸模拟验证

准确估算陆地生态系统呼吸(Ecosystem respiration,RE)对全球陆地生态系统碳收支研究具有重要意义.模型模拟是估算陆地RE变化的一种常用手段.然而目前陆地生态系统过程模型的RE模拟尚未得到充分验证.基于耦合模式比较计划第五阶段(Coupled Model Intercomparison Project Phase 5,CMIP5)的通用陆面模型(Community land model,CLM)RE模拟结果和全球通量网(FLUXNET)66个站点的涡度相关通量观测数据(277条站点年数据)评估CLM模型对RE的模拟效果.结果表明:~(1)在空间尺度上,CLM低估了高纬度站点RE,高估了低纬度站点RE,但高纬度低估量更大导致空间格局整体低估(相对误差为-3.56%).(2)在时间尺度上,CLM模型基本捕捉了RE的年际和季节变化,相关系数分别为0.60(P0.001)和0.63(P0.001);CLM低估年尺度和月尺度的RE(以C计_),绝对误差分别是-182.21 g m-~(2 )a-~1、-120.16 g m-~(2 )mon-~1,相对误差分别是-17.84%、-10.60%.(3)CLM模型对不同植被功能型的RE模拟效果不同,由优及差依次为混交林、常绿针叶林、草地、农田、落叶阔叶林、常绿阔叶林.本研究在时空尺度上量化了CLM模型的生态系统呼吸模拟误差,并分析了土壤呼吸Q10和MRbase参数以及土壤碳库模拟等因素的影响,可为CLM模型的生态系统呼吸模块参数优化提供依据,进而提升其模拟精度.(图4表3参80附图2附表2)     

我国集约化种植业面源氮发生量估算

面源污染已经成为一个世界性问题,当前大尺度面源氮负荷核算方法主要通过区域收支法或考虑氮肥用量的输出系数法,存在很大的不确定性。基于全国187组文献数据,应用逐步回归分析方法,提取影响种植业面源氮发生量(氮素径流和淋洗)的关键因子,构建了关于氮肥用量、降雨量和土壤黏粒含量的多元回归模型。应用2011年统计年鉴数据,模拟得到全国种植业氮素径流总损失量为0. 96 Tg,占氮肥投入量的6. 0%,其中,旱地和水田径流损失量分别为0. 76和0. 20 Tg。而全国种植业氮素淋洗总损失量为1. 01 Tg,占氮肥投入量的6. 3%,其中,旱地和水田淋洗损失量分别为0. 87和0. 14 Tg。面源氮发生量较高的区域位于长江中下游地区、西南丘陵地区、山东半岛和华北平原。所建模型不仅能估算我国集约化种植业面源氮发生量分布情况,而且与传统的考虑单一氮肥用量的排放系数模型相比,能大大降低大区域尺度估算的不确定性。     

Numerical experiments with RAMS model in highly complex terrain

RAMS mesoscale model has been applied to simulate the atmospheric circulation in highly complex terrain, in the Hindu-Kush Karakorum and Himalaya regions. The goal of the work is to assess the sensitivity of the model to the grid spacing and related resolution, the smoothing of the orography, the microphysics parameterizations, in such heterogeneous and challenging conditions. As a follow up, the capability of the model in correctly capturing the atmospheric processes is tested. Two main cases, where some measured data were available, have been considered: a period during which a flood occurred and a period characterised by high-pollution episodes. RAMS model provided sensible results, the predictions reasonably reproduce the observed data at a regional scale, but the most local characteristics cannot be definitely described even at the typical resolution of 1 km order.     

Emergy algebra: Improving matrix methods for calculating transformities

Transformity is one of the core concepts in Energy Systems Theory and it is fundamental to the calculation of emergy. Accurate evaluation of transformities and other emergy per unit values is essential for the broad acceptance, application and further development of emergy methods. Since the rules for the calculation of emergy are different from those for energy, particular calculation methods and models have been developed for use in the emergy analysis of networks, but double counting errors still occur because of errors in applying these rules when estimating the emergies of feedbacks and co-products. In this paper, configurations of network energy flows were classified into seven types based on commonly occurring combinations of feedbacks, splits, and co-products. A method of structuring the network equations for each type using the rules of emergy algebra, which we called “preconditioning” prior to calculating transformities, was developed to avoid double counting errors in determining the emergy basis for energy flows in the network. The results obtained from previous approaches, the Track Summing Method, the Minimum Eigenvalue Model and the Linear Optimization Model, were reviewed in detail by evaluating a hypothetical system, which included several types of interactions and two inputs. A Matrix Model was introduced to simplify the calculation of transformities and it was also tested using the same hypothetical system. In addition, the Matrix Model was applied to two real case studies, which previously had been analyzed using the existing method and models. Comparison of the three case studies showed that if the preconditioning step to structure the equations was missing, double counting would lead to large errors in the transformity estimates, up to 275 percent for complex flows with feedback and co-product interactions. After preconditioning, the same results were obtained from all methods and models. The Matrix Model reduces the complexity of the Track Summing Method for the analysis of complex systems, and offers a more direct and understandable link between the network diagram and the matrix algebra, compared with the Minimum Eigenvalue Model or the Linear Optimization Model.     

Remote sensing of crop production in China by production efficiency models: models comparisons,estimates and uncertainties

Regional estimates or prediction of crop production is critical for many applications such as agricultural lands management, food security warning system, food trade policy and carbon cycle research. Remote sensing offers great potential for regional production monitoring and estimates, yet uncertainties associated with are rarely addressed. Moreover, although crops are one of critical biomes in global carbon cycle research, few evidences are available on the performance of global models of terrestrial net primary productivity (NPP) in estimating regional crop NPP. In this study, we use high quality weather and crop data to calibrate model parameter, validate and compare two kinds of remote sensing based production efficiency models, i.e. the Carnegie-Ames-Stanford-Approach (CASA) and Global Production Efficiency Model Version 2.0 (GLO-PEM2), in estimating maize production across China. Results show that both models intend to underestimate maize yields, although they also overestimate maize yields much at some regions. There are no significant differences between the results from CASA and GLO-PEM2 models in terms of both estimated production and spatial pattern. CASA model simulates better in the areas with dense crop and weather data for calibration. Otherwise GLO-PEM2 model does better. Whether the water soil-moisture down-regulator is used or not should depend on the percent of irrigation lands at the regions. The improved and validated models can be used for many applications. Further improvement can be expected by increasing remote sensing image resolution and the number of surface data stations.     

Local complexity in patterns of canopy–benthos associations produces regional patterns across temperate Australasia

Across subtidal coasts of temperate Australasia, canopy–benthos associations are mostly understood from broadly defined studies of kelp forests within eastern Australia and north-eastern New Zealand. We tested the hypotheses that (1) benthic assemblages differ between monospecific stands of Ecklonia radiata and stands that comprise E. radiata mixed with other canopy-forming species, (2) patterns observed locally (i.e. within sites 1–10 km apart) match those observed among regions (>1,000 km apart) for which (3) eastern Australia and northern New Zealand are representative of other regions of temperate Australasia. Benthic assemblages almost always differed among monospecific, mixed, and open stands indicating that failure to distinguish between superficially similar habitats can lead to over-generalised conclusions about the ecology of kelp forests. Patterns of differences among stands did not change between western and southern Australia but differed from eastern Australia, and patterns from all regions were distinct from New Zealand (WA=SAEANZ). Whilst local patterns were complex, the major morphological groups that often characterise benthos (i.e. encrusting coralline algae and turf-forming algae) revealed patterns that could be related across space from local to regional scales. These findings demonstrate that knowledge about the configuration of canopy-forming species will improve confidence about the representativeness of results and that any local complexity need not impede searches for generality when the spatial limits of patterns are also understood.Communicated by M.S. Johnson, Crawley     

密云水库上游地区农田土壤有机碳储量及变化模拟

农田土壤有机碳(SOC)库对粮食安全和全球气候变化具有重要影响,因此,开展农田土壤有机碳储量及其动态变化研究在政治经济和生态环境层面具有重要意义.采用农业生物地球化学模型--DNDC对密云水库上游地区农田土壤有机碳储量及其变化进行模拟研究,首先应用当地实测结果进行模型验证,然后根据当地气候条件、土壤性质和现行农业耕作管理特点等建立GIS区域数据库,并在数据库的支持下进行区域模拟和分析.结果表明:2006年密云水库上游地区214 920 hm~2农田土壤(0～25 cm)的总有机碳储量为7 646×10~6 kg,其中位于河北省境内的该地区63.1%的农田储存了全区68.1%的SOC;平均每公顷农田SOC储量为35 576.1 kg,低于全国平均水平;由于化肥和有机肥投入的增加,经过1 a耕种后,2006年该地区农田SOC储量增加142.5×10~6 kg,整个地区及各区县农田土壤碳收支均为正,是大气CO_2的一个汇.情景分析表明,气温升高对该地区农田SOC积累具有显著的负效应;而提高秸秆还田比例、适量施用化肥、增施有机肥、增加灌溉和采取免耕方式等措施均能有效增加土壤有机碳的积累.     

Effects of regional vs. ecological factors on plant species richness: an intercontinental analysis

Conclusions from past studies on the roles that historical and regional factors and contemporary and ecological factors have played in regulating large-scale patterns of species richness have been controversial. Conflicting past results were likely affected by differences in the range of environments analyzed and the scales of observation. Eastern North America and eastern Asia are ideal regions for examining the relative effects of historical and regional factors and contemporary and ecological factors on large-scale patterns of plant species richness because these two regions are closely matched in terms of climate and because their floras originated from the same paleoflora but have experienced different histories of development since the late Paleogene when climate cooling caused their separation. We report on a comprehensive data set of 471 floras ranging from 10 km2 to 4.7 x 10(6) km2 and spanning a wide range of climate and latitude (from 21 degrees to 55 degrees N) to examine whether the contribution of region relative to climate persists from small to large floras and increases from cooler to warmer climates. We found that eastern Asia is richer than eastern North America when sample area, maximum elevation, and climate are accounted for, that this difference diminishes toward higher latitudes, and that elevation plays a much stronger role in eastern Asia than in eastern North America. Our analysis reconciles contemporary/ecological and historical/regional explanations for species richness variation and helps explain why different conclusions have been reached by different authors working in the same geographical areas: the strength of the region effect itself varies with location and range of climatic conditions of the observations.     

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.     

Multi-model approach and evaluation of the uncertainty of model results. Rationale and applications to predict the behaviour of contaminants in the abiotic components of the fresh water environment

This work aims at discussing some concepts pertaining to the theory and practice of environmental modelling in view of the results of several model validation exercises performed by the group “Model validation for radionuclide transport in the system watershed-river and in estuaries” of project EMRAS (Environmental Modelling for Radiation Safety) supported by the IAEA (International Atomic Energy Agency). The analyses here performed concern models applied to real scenarios of environmental contamination. In particular, the reasons for the uncertainty of the models and the EBUA (empirically based uncertainty analysis) methodology are discussed. The foundations of multi-model approach in environmental modelling are presented and motivated. An application of EBUA to the results of a multi-model exercise concerning three models aimed at predicting the wash-off of radionuclide deposits from the Pripyat floodplain (Ukraine) was described. Multi-model approach is, definitely, a tool for uncertainty analysis. EBUA offers the opportunity of an evaluation of the uncertainty levels of predictions in multi-model applications.     

Trends in sea ice cover within habitats used by bowhead whales in the western Arctic.

We examined trends in sea ice cover between 1979 and 2002 in four months (March, June, September, and November) for four large (approximately 100,000 km2) and 12 small (approximately 10,000 km2) regions of the western Arctic in habitats used by bowhead whales (Balaena mysticetus). Variation in open water with year was significant in all months except March, but interactions between region and year were not. Open water increased in both large and small regions, but trends were weak with least-squares regression accounting for < or =34% of the total variation. In large regions, positive trends in open water were strongest in September. Linear fits were poor, however, even in the East Siberian, Chukchi, and Beaufort seas, where basin-scale analyses have emphasized dramatic sea ice loss. Small regions also showed weak positive trends in open water and strong interannual variability. Open water increased consistently in five small regions where bowhead whales have been observed feeding or where oceanographic models predict prey entrainment, including: (1) June, along the northern Chukotka coast, near Wrangel Island, and along the Beaufort slope; (2) September, near Wrangel Island, the Barrow Arc, and the Chukchi Borderland; and (3) November, along the Barrow Arc. Conversely, there was very little consistent change in sea ice cover in four small regions considered winter refugia for bowhead whales in the northern Bering Sea, nor in two small regions that include the primary springtime migration corridor in the Chukchi Sea. The effects of sea ice cover on bowhead whale prey availability are unknown but can be modeled via production and advection pathways. Our conceptual model suggests that reductions in sea ice cover will increase prey availability along both pathways for this population. This analysis elucidates the variability inherent in the western Arctic marine ecosystem at scales relevant to bowhead whales and contrasts basin-scale depictions of extreme sea ice retreats, thinning, and wind-driven movements.