生态足迹计算模型应用中热点问题及探讨

简要介绍了生态足迹计算模型,论述了近年国际上争论的几个主要热点问题,数据的准确完整性,初级产品与二级产品,均衡因子与产量因子,全球产量与本地产量,以及能源足迹计算等,并对其进行了探讨和指出今后研究发展的方向。     

Performance Evaluation of the SLEUTH Model in the Shenyang Metropolitan Area of Northeastern China

Performance evaluation is crucial for the development and improvement of an urban cellular automata model, such as SLEUTH. In this paper, we employed multiple methods for map comparison and model validation to evaluate the simulation performance of the SLEUTH urban growth model in the Shenyang metropolitan area of China. These multiple methods included the relative operating characteristic (ROC) curve statistic, multiple-resolutions error budget, and landscape metrics. They were used to quantitatively examine model performance in terms of the amount and spatial location of urban development, urban spatial pattern and prediction ability. The assessment results showed that SLEUTH performed well in the way of the quantitative simulation of urban growth for this case study. Similar to other urban growth models, however, the simulation accuracy for spatial location of new development at the pixel scale and urban spatial pattern still needs to be improved greatly. These inaccuracies might be attributed to the structure and nature of SLEUTH, local urban development characteristics, and the temporal and spatial scale of its application. Finally, many valuable suggestions had been put forward to improve simulation performance of SLEUTH model for spatial location of urban development in the Shenyang metropolitan area.     

江苏省空气质量预报与实测结果比对研究

选取2015年1—8月江苏地区NAQPMS、CMAQ、CAMx、WRF-Chem 4个模式预报结果与实测值进行比对分析,结果表明,标准化分数偏差(MFB)为-0.066 5~0.201 1,标准化分数误差(MFE)最大值为0.381 8,均在理想范围内,其中CAMx预报效果相对较好,WRF-Chem有一定误差。4个模式相比,NAQPMS对于PM_(10)的模拟性能较好,各模式对PM_(2.5)模拟性能相近,CMAQ和CAMx对O_3模拟较好,WRF-Chem对CO模拟较好,各模式对SO_2和NO_2的模拟都需进一步优化。     

生物配体模型的适用性研究

简要介绍了生物配体模型(Biotic Ligand Model,BLM)的发展以及理论基础,对模型的优势和应用中存在的问题进行了分析,并对模型研究的发展趋势进行了展望。     

公路隧道可吸入颗粒物扩散模型研究

运用大气扩散理论,得到了隧道内自然通风和纵向通风状态下的可吸入颗粒物(PM10)扩散模型,并由隧道口PM10浓度、隧道截面积、隧道内风速,以及车流量和类型等参数,获得了整条隧道内的不同PM10浓度分布.模型表明,随着隧道深度的增加,PM10浓度逐渐增大.通过采用纵向通风的玄武湖隧道各参数,得到了3组不同条件下的PM10扩散模型,并用所得模型计算了隧道内不同深度处PM10的浓度.沿隧道不同深度测得的PM10浓度值的比较结果表明,实际测定值围绕计算值上下波动,两者之间具有良好的一致性.     

Predicting aquaculture-derived benthic organic enrichment: Model validation

A sediment trap validation study was conducted near the commercial sea bass and sea bream fish farm in order to assess the predictive capability of a particle tracking deposition model. The validation procedure consisted of two distinct phases. First, the deposition of particulate waste (i.e. fecal pellets and excess feed) was measured near a single net pen containing 19 tons of sea bass. Afterwards, the model quality was determined by statistical comparison of predicted and observed values.Goodness of fit analysis indicates that the model successfully accounts for more than 75% of variance in the observed deposition. At 5% significance level, predictions do not underestimate or overestimate observations and there is no bias. Mean absolute relative error of ±48.9% compares favorably to other published deposition models. Obtained results affirm the reliability of particle tracking techniques in modeling the aquaculture-derived benthic organic enrichment.     

Structural changes in lake functioning induced from nutrient loading and climate variability

Climate variability is increasingly recognized as an important regulatory factor, capable of influencing the structural properties of aquatic ecosystems. Lakes appear to be particularly sensitive to the ecological impacts of climate variability, and several long time series have shown a close coupling between climate, lake thermal properties and individual organism physiology, population abundance, community structure, and food web dynamics. Thus, understanding the complex interplay among meteorological forcing, hydrological variability, and ecosystem functioning is essential for improving the credibility of model-based water resources/fisheries management. Our objective herein is to examine the relative importance of the ecological mechanisms underlying plankton seasonal variability in Lake Washington, Washington State (USA), over a 35-year period (1964–1998). Our analysis is founded upon an intermediate complexity plankton model that is used to reproduce the limiting nutrient (phosphate)–phytoplankton–zooplankton–detritus (particulate phosphorus) dynamics in the lake. Model parameterization is based on a Bayesian calibration scheme that offers insights into the degree of information the data contain about model inputs and allows obtaining predictions along with uncertainty bounds for modeled output variables. The model accurately reproduces the key seasonal planktonic patterns in Lake Washington and provides realistic estimates of predictive uncertainty for water quality variables of environmental management interest. A principal component analysis of the annual estimates of the underlying ecological processes highlighted the significant role of the phosphorus recycling stemming from the zooplankton excretion on the planktonic food web variability. We also identified a moderately significant signature of the local climatic conditions (air temperature) on phytoplankton growth (r = 0.41), herbivorous grazing (r = 0.38), and detritus mineralization (r = 0.39). Our study seeks linkages with the conceptual food web model proposed by Hampton et al. [Hampton, S.E., Scheuerell, M.D., Schindler, D.E., 2006b. Coalescence in the Lake Washington story: interaction strengths in a planktonic food web. Limnol. Oceanogr. 51, 2042–2051.] to emphasize the “bottom-up” control of the Lake Washington plankton phenology. The posterior predictive distributions of the plankton model are also used to assess the exceedance frequency and confidence of compliance with total phosphorus (15 μg L⁻¹) and chlorophyll a (4 μg L⁻¹) threshold levels during the summer-stratified period in Lake Washington. Finally, we conclude by underscoring the importance of explicitly acknowledging the uncertainty in ecological forecasts to the management of freshwater ecosystems under a changing global environment.     

A derivation of the statistical characteristics of forest fires

The analysis of large data sets concerning fires in various forested areas of the world has pointed out that burned areas can often be described by different power-law distributions for small, medium and large fires and that a scaling law for the time intervals separating successive fires is fulfilled. The attempts of deriving such statistical laws from purely theoretical arguments have not been fully successful so far, most likely because important physical and/or biological factors controlling forest fires were not taken into account. By contrast, the two-layer spatially extended forest model we propose in this paper encapsulates the main characteristics of vegetational growth and fire ignition and propagation, and supports the empirically discovered statistical laws. Since the model is fully deterministic and spatially homogeneous, the emergence of the power and scaling laws does not seem to necessarily require meteorological randomness and geophysical heterogeneity, although these factors certainly amplify the chaoticity of the fires. Moreover, the analysis suggests that the existence of different power-laws for fires of various scale might be due to the two-layer structure of the forest which allows the formation of different kinds of fires, i.e. surface, crown, and mixed fires.     

A comparison of four process-based models and a statistical regression model to predict growth of Eucalyptus globulus plantations

In forest management and ecological research, consideration of the impacts and risks of climate change or management optimisation is complex. Computer models have long been applied as tools for these tasks. Process-based forest growth models claim to overcome the limitations of empirical statistical models, but the capacity of different process-based models and modelling approaches have rarely been compared directly. This study evaluates stepwise multiple regression models in comparison to four process-based modelling approaches (3-PG, 3-PG+, CABALA and Forest-DNDC) for greenfield predictions of Eucalyptus globulus plantation growth from 2 to 8 years after planting throughout southern Australia.     

The puzzle of North America's Late Pleistocene megafaunal extinction patterns: Test of new explanation yields unexpected results

Although Late Pleistocene extinctions disproportionately affected larger mammalian species, numerous smaller species were also lost. To date, no satisfactory explanation has been presented to account for this pattern. Beginning with the assumption that human predation caused the extinctions, we offer and test the first such explanatory hypothesis, which is predicated on considering more realistic functional response forms (i.e., those that allow for predator interference or prey sharing). We then test the hypothesis via a one-predator, six-prey ecological model that maintains transparency, minimalism of design, and maximal constraint of parameters. Results indicate that altering assumptions about one cornerstone of ecological modeling (i.e., functional response) fails to produce qualitative differences in survival–extinction outcomes—even in conjunction with a wide range of capture efficiency permutations. This unexpected finding suggests that no reasonable form of predation alone is capable of producing the survival–extinction pattern observed. We conclude that the matter of causation and the conclusions of previous Late Pleistocene extinction models remain far less certain than many have assumed.