“传统”农业景观旅游保护困局的反思（英文）

全球范围对"文化景观"重新燃起兴趣需要从多维方式来解释。传统栖息地,人民和他们在特殊环境里的生活方式的价值改变过程是和与遗产地有关的"文化、社会和经济建设"的引入密不可分的。自上世纪90年代开始,文化景观作为一种新型遗产列入联合国教科文组织世界遗产名录,它强调人类与环境相互作用的重要性,需要了解景观在时空上的动态性。观念的变化产生了对标志性景观和传统社区的"动态保护"。从交叉学科的视角来理解这一交互过程对规划和保护可持续遗产景观至关重要。遍及全世界的各试点项目和案例研究都引起了关于遗产景观的可持续性和旅游的至高无上作用的批判性反思。全球重要农业文化遗产(GIAHS)能否受益于旅游产生的经济资源,需要基于研究的方法来分析机会和预期,评估其战略政策和自上而下的政策。     

Cost–benefit analysis of climate change dynamics: uncertainties and the value of information

We analyze climate change in a cost–benefit framework, using the emission and concentration profiles of Wigley et al. (Nature 379(6562):240–243, 1996). They present five scenarios that cover the period 1990–2300 and are designed to reach stabilized concentration levels of 350, 450, 550, 650 and 750 ppmv, respectively. We assume that the damage cost in each year t is proportional to the corresponding gross world product and the square of the atmospheric temperature increase (ΔT(t)). The latter is estimated with a simple two-box model (representing the atmosphere and deep ocean). Coupling the damage cost with the abatement cost, we interpolate between the five scenarios to find the one that is optimal in the sense of minimizing the sum of discounted annual (abatement plus damage) costs over a time horizon of N years. Our method is simpler than ‘traditional’ models with the same purpose, and thus allows for a more transparent sensitivity study with respect to the uncertainties of all parameters involved. We report our central result in terms of the stabilized emission level E _o and concentration level p _o (i.e. their values at t = 300 years) of the optimal scenario. For the central parameter values (that is, N = 150 years, a discount rate r _dis = 2%/year and a growth rate r _gro = 1%/year of gross world product) we find E _o  = 8.0 GtCO₂/year and p _o = 496 ppmv. Varying the parameters over a wide range, we find that the optimal emission level remains within a remarkably narrow range, from about 6.0 to 12 GtCO₂/year for all plausible parameter values. To assess the significance of the uncertainties we focus on the social cost penalty, defined as the extra cost incurred by society relative to the optimum if one makes the wrong choice of the emission level as a result of erroneous damage and abatement cost estimates. In relative terms the cost penalty turns out to be remarkably insensitive to errors. For example, if the true damage costs are three times larger or smaller than the estimate, the total social cost of global climate change increases by less than 20% above its minimum at the true optimal emission level. Because of the enormous magnitude of the total costs involved with climate change (mitigation), however, even a small relative error implies large additional expenses in absolute terms. To evaluate the benefit of reducing cost uncertainties, we plot the cost penalty as function of the uncertainty in relative damage and abatement costs, expressed as geometric standard deviation and standard deviation respectively. If continued externality analysis reduces the geometric standard deviation of relative damage cost estimates from 5 to 4, the benefit is 0.05% of the present value G _tot of total gross word product over 150 years (about $3.9 × 10¹⁵), and if further research reduces the standard deviation of relative abatement costs from 1 to 0.5, the benefit is 0.03% of G _tot .     

Trend analysis of long-term temperature time series in the Greater Toronto Area (GTA)

As the majority of the world’s population is living in urban environments, there is growing interest in studying local urban climates. In this paper, for the first time, the long-term trends (31–162 years) of temperature change have been analyzed for the Greater Toronto Area (GTA). Annual and seasonal time series for a number of urban, suburban, and rural weather stations are considered. Non-parametric statistical techniques such as Mann–Kendall test and Theil-Sen slope estimation are used primarily for the assessing of the significance and detection of trends, and the sequential Mann test is used to detect any abrupt climate change. Statistically significant trends for annual mean and minimum temperatures are detected for almost all stations in the GTA. Winter is found to be the most coherent season contributing substantially to the increase in annual minimum temperature. The analyses of the abrupt changes in temperature suggest that the beginning of the increasing trend in Toronto started after the 1920s and then continued to increase to the 1960s. For all stations, there is a significant increase of annual and seasonal (particularly winter) temperatures after the 1980s. In terms of the linkage between urbanization and spatiotemporal thermal patterns, significant linear trends in annual mean and minimum temperature are detected for the period of 1878–1978 for the urban station, Toronto, while for the rural counterparts, the trends are not significant. Also, for all stations in the GTA that are situated in all directions except south of Toronto, substantial temperature change is detected for the periods of 1970–2000 and 1989–2000. It is concluded that the urbanization in the GTA has significantly contributed to the increase of the annual mean temperatures during the past three decades. In addition to urbanization, the influence of local climate, topography, and larger scale warming are incorporated in the analysis of the trends.     

Discrimination test between the Halphen (A and B) and the gamma distributions

Hydrological frequency analysis is the most widely used method to estimate risk for extreme values. The most used statistical distributions to fit extreme value data in hydrology can be regrouped in three classes: class C of regularly varying distributions, class D of sub exponential and class E, Exponential depending on their tail behavior. The Halphen distributions (Halphen type A (HA), Halphen type B (HB)) are separated by the Gamma distribution; these three distributions belong to class D and can be displayed in the (δ₁, δ₂) moment-ratio diagram. In this study, a statistical test for discriminating between HA, HB and the Gamma distribution is developed. The methodology is based on: (1) the generation of N samples of different sizes n around the Gamma curve; (2) the determination of the confidence zones around the Gamma curve for each fixed couple (δ₁, δ₂) moment-ratios and finally; (3) the study of the power of the test developed and the calculation of the type 2 error β and the power of the test which is 1-β for a fixed significance level α. Results showed that the test is powerful especially for high coefficients of skewness. This test will be included in Decision Support System of the HYFRAN-PLUS software.     

A new method for estimating high-frequency radar error using data from Central San Francisco Bay

This study offers a new method for estimating High-Frequency (HF) radar surface current velocity error in data comparisons with other types of instrumentation. A new method is needed in order to remove the zero-mean random spatial and temporal fluctuations present in surface-current measurements from all sensors. Conventional methods for calculating radar error when comparing with another instrument have included their root mean square differences and scatter plots that provide correlation coefficient and slope/intercept of the regression line. It seems that a meaningful estimate of radar error should attempt to remove both sensors’ zero mean random fluctuations, inasmuch as possible. We offer and compare a method that does this. The method was tested on data collected in the Central San Francisco Bay, where GPS surface-drifter deployments were conducted within the coverage of four 42 MHz radars over six days in October of 2008. Drifters were continuously deployed in these areas over the sampling days, providing 525 usable drifter measurements. Drifter and radar measurements were averaged into thirty-minute time bins. The three-day long-term averages from the sampling areas were then subtracted from the thirtyminute averages to remove biases associated with comparisons done with short, disjoint time-sample periods. These were then used to develop methods that give radar error or bias after the random fluctuations have been removed. Results for error estimates in this study are commensurate with others where random fluctuations have been filtered, suggesting they are valid. The estimated error for the radars in the SF Bay is low, ranging from ?7.57 cm/s to 0.59 cm/s.     

Examining past temperature variability in Moosonee, Thunder Bay, and Toronto, Ontario, Canada through a day-to-day variability framework

Temperature variability in Moosonee, Thunder Bay, and Toronto, Ontario, Canada is examined through a day-to-day variability framework. Statistical measures used in this study include standard deviation (SD), day-to-day temperature variability (DTD), DTD/SD ratio (G), change in day-to-day variability (ΔDTD), and threshold measures of 5°C and 10°C. ΔDTD is the difference between day-to-day change in temperature maximum (DTDtmax) and day-to-day change in temperature minimum (DTDtmin). A distinct seasonal trend is reflected in DTD in Moosonee, Thunder Bay, and Toronto, where ΔDTD is greatest during spring. Monthly ΔDTD averages in Toronto, Thunder Bay, and Moosonee are affected by seasonal variation, the lake effect, and the freeze-up of nearby waterbodies. Yearly averages of ΔDTD have significantly increased over the past recent years in Moosonee and Thunder Bay; a continual increase in climate variability may be detrimental to the subsistence lifestyle of those living in these areas.     

Global Oscillations at Low Frequency from the SOHO mission (GOLF)

The GOLF experiment on the SOHO mission aims to study the internal structure of the sun by measuring the spectrum of global oscillations in the frequency range 10^–7 to 10^–2 Hz. Bothp andg mode oscillations will be investigated, with the emphasis on the low order long period waves which penetrate the solar core. The instrument employs an extension to space of the proven ground-based technique for measuring the mean line-of-sight velocity of the viewed solar surface. By avoiding the atmospheric disturbances experienced from the ground, and choosing a non-eclipsing orbit, GOLF aims to improve the instrumental sensitivity limit by an order of magnitude to 1 mm s^–1 over 20 days for frequencies higher than 2.10^–4 Hz. A sodium vapour resonance cell is used in a longitudinal magnetic field to sample the two wings of the solar absorption line. The addition of a small modulating field component enables the slope of the wings to be measured. This provides not only an internal calibration of the instrument sensitivity, but also offers a further possibility to recognise, and correct for, the solar background signal produced by the effects of solar magnetically active regions. The use of an additional rotating polariser enables measurement of the mean solar line-of-sight magnetic field, as a secondary objective.