Structurally-consistent estimation of use and nonuse values for landscape-wide environmental change

We address the problem of estimating the use and nonuse value derived from a landscape-wide programme of environmental change. Working in the random utility framework, we develop a structural model that describes both demand for recreational trips to the landscape's quality-differentiated natural areas and preferences over different landscape-wide patterns of environmental quality elicited in a choice experiment. The structural coherence of the model ensures that the parameters of the preference function can be simultaneously estimated from the combination of revealed and stated preference data. We explore the properties of the model in a Monte Carlo experiment and then apply it to a study of preferences for changes in the ecological quality of rivers in northern England. This implementation reveals plausible estimates of the use and nonuse parameters of the model and provides insights into the distance decay in those two different forms of value.     

Effects of spatial autocorrelation and sampling design on estimates of protected area effectiveness

Estimating the effectiveness of protected areas (PAs) in reducing deforestation is useful to support decisions on whether to invest in better management of areas already protected or to create new ones. Statistical matching is commonly used to assess this effectiveness, but spatial autocorrelation and regional differences in protection effectiveness are frequently overlooked. Using Colombia as a case study, we employed statistical matching to account for confounding factors in park location and accounted for for spatial autocorrelation to determine statistical significance. We compared the performance of different matching procedures—ways of generating matching pairs at different scales—in estimating PA effectiveness. Differences in matching procedures affected covariate similarity between matched pairs (balance) and estimates of PA effectiveness in reducing deforestation. Independent matching yielded the greatest balance. On average 95% of variables in each region were balanced with independent matching, whereas 33% of variables were balanced when using the method that performed worst. The best estimates suggested that average deforestation inside protected areas in Colombia was 40% lower than in matched sites. Protection significantly reduced deforestation, but PA effectiveness differed among regions. Protected areas in Caribe were the most effective, whereas those in Orinoco and Pacific were least effective. Our results demonstrate that accounting for spatial autocorrelation and using independent matching for each subset of data is needed to infer the effectiveness of protection in reducing deforestation. Not accounting for spatial autocorrelation can distort the assessment of protection effectiveness, increasing type I and II errors and inflating effect size. Our method allowed improved estimates of protection effectiveness across scales and under different conditions and can be applied to other regions to effectively assess PA performance.     

Using chemical models for evaluating the geochemical confinement capacity of a geological barrier application to the Centre de Stockage de l'Aube (France)

The feasibility of using a chemical reaction-based approach for evaluating and modelling the role of adsorption reactions in determining the geochernical confinement capacity of natural geological barriers is being studied as part of an on-going R & D programme. The confined superficial aquifer underlying the Centre de Stockage de l'Aube facility, a geological barrier for this site, has been used as a case study with the following aims. First, development of a site characterisation protocol and demonstration of its use to determine the principal geochemical characteristics of aquifer materials using batch experiments and to represent the information obtained in terms of a chemical model. The experimental results obtained for Ni²⁺ partitioning as a function of total Ni, pH, total Ca and total solid can be satisfactorily represented in terms of reactions with an ion exchange site and a single amphoteric surface hydroxyl site with ferrihydrite reaction constants. A second objective is the incorporation of the reactions in a coupled geochemistry/transport code, and to verify the applicability of the coupled code predictions for Ni²⁺ mass transfer by comparison with the results obtained during column tracer experiments. The breakthrough curve and equilibrium solid phase Ni loading, predicted by a one-dimensional coupled model for a column tracer experiment, agree closely with observed data.Additional studies are underway to reduce model conditionality, to extend the adsorption model to other analogue cations and anions, to incorporate the effect of natural organic matter and to take into consideration precipitation/dissolution of amorphous Fe surface phases.     

高氮营养增高厚果含笑叶片的叶黄素介导热耗散研究

厚果含笑(Michelialacei)生长在供给6mmolL-1NO3-(高氮)和2mmolL-1NO3-(低氮)Hoagland溶液的盆栽土中,利用PAM-2100叶绿素荧光仪、Licor-6400LCF荧光叶室和WatersHPLC分别测定叶绿素a荧光参数和类胡萝卜素组分,研究氮营养对光系统II(PSII)光化效率和光或暗下热耗散过程的影响.结果表明,在自然光日进程中叶片的开启PSII反应中心的内在量子效率(Fv/Fm)随光辐射增强而降低.低氮叶片Fv/Fm较高氮叶片降低明显(P<0.05).低氮叶片表现较明显的光抑制现象,反映低氮叶片对光抑制比高氮叶片敏感.高氮叶片比低氮叶片有低的PSII光化效率(ΦPSⅡ,P<0.05).高氮叶片依赖光的ΔpH和叶黄素介导的热耗散效率(ΦNPQ)和光下热耗散速率(JNPQ)则较低氮叶片高(P<0.05),结果反映高氮营养增进光下热耗散效率和速率.高氮叶片的紫黄质(A) 玉米黄质(Z)和叶黄素循环色素的转换态(A Z/V A Z)则较低氮叶片高(P<0.05).高氮叶片有较高光下热耗散(NPQ)和相应较高的(A Z)或(A Z/V A Z),叶片通过叶黄素循环色素以热的形式耗散过剩能;而低氮叶片表现高的总荧光淬灭和暗下热耗散.充足氮叶片有较低的光化效率,增高了光呼吸,并通过增强通过叶黄素循环色素的大量耗散过剩能.结果显示,过量氮输入将降低植物光能利用效率.图6表3参28     

一个适用于区域性大气环境模拟的大气光化学模式

根据“计数物种”法对光化学反应机制的分析,建立了一个适用于区域性光化学反应模拟的模式,该模式能较好地模拟出NO_x、O_3及H_2O_2等大气光化学污染物的变化,在保证模拟准确性的同时,该模式形式简单,有利于在实际大气环境质量模拟中应用.     

MULTIPLICATIVE,SEASONAL ARIMA MODELS FOR LAKE ERIE AND LAKE ONTARIO WATER LEVELS1

ABSTRACT: Federal agencies in the U.S. and Canada continuously examine methods to improve understanding and forecasting of Great Lakes water level dynamics in an effort to reduce the negative impacts of fluctuating levels incurred by interests using the lakes. The short term, seasonal and long term water level dynamics of lakes Erie and Ontario are discussed. Multiplicative, seasonal ARIMA models are developed for lakes Erie and Ontario using standardized, monthly mean level data for the period 1900 to 1986. The most appropriate model identified for each lake had the general form: (1 0 1)(0 1 1)₁₂. The data for each lake were subdivided by time periods (1900 to 1942;1 943 to 1986) and the model coefficients estimated for the subdivided data were similar, indicating general model stability for the entire period of record. The models estimated for the full data sets were used to forecast levels 1,2,3, and 6 months ahead for a period of high levels (1984 to 1986). The average absolute forecast error for Lake Erie was 0.049m, 0.076m, 0.091 m and 0.128m for the 1, 2,3, and 6 month forecasts, respectively. The average absolute forecast error for Lake Ontario was 0.058m, 0.095m, 0.120m and 0.136m for the 1,2,3, and 6 month forecasts, respectively. The ARIMA models provide additional information on water level time series structure and dynamics. The models also could be coordinated with current forecasting methods, possibly improving forecasting accuracy.     

A DISTRIBUTED DYNAMIC WATERSHED MODEL1

ABSTRACT: A distributed watershed model was developed to mathematically simulate overland and channel flow for a single-event storm. The modeled watersheds in the study were subdivided into rectangular grid elements. All hydrologically significant parameters, such as land slope, rainfall and precipitation excess, were assumed to be uniform within each element. The Green-Ampt method was adopted to generate precipitation excess for each element during the simulation period. A two-dimensional diffusion wave model was used for overland flow routing and an iterative Alternative Direction Implicit scheme was used to solve the simultaneous overland flow equations. Once the overland flow became inflow to the channel, a one-dimensional dynamic wave flood routing technique, based on a four-point, implicit, non-linear finite difference solution of the St. Venant equation of unsteady flow, was applied. A limited number of comparisons were made between simulated and observed hydrographs for areas of about one square mile. Given the appropriate parameters, the model was able to accurately simulate runoff for single-event storms. This paper describes a distributed watershed model developed to simulate overland and channel flow. Comparisons were made between simulated and observed hydrographs for three watersheds. The model was able to accurately simulate the runoff for single-event storms using 61-m by 61-m (200 ft by 200 ft) watershed grid elements.     

Island biogeographical theory: Can it be used to predict lotic recovery rates?

Classic island biogeographic theory predicts that equilibrium will be reached when immigration and extinction rates are equal. These rates are modified by number of species in source area, number of intermediate islands, distance to recipient island, and size of intermediate islands. This general model has been variously modified and proposed to be a stochastic process with minimal competitive interaction or heavily deterministic. Predictive models of recovery (regardless of the end point chosen) have been based on the appropriateness of the MacArthur-Wilson models. Because disturbance frequency, severity, and intensity vary in their effect on community dynamics, we propose that disturbance levels should first be defined before evaluating the applicability of island biogeographical theory. Thus, we suggest a classification system of four disturbance levels based on recovery patterns by primary and secondary succession and faunal organization by primary (invasion of vacant areas) and secondary (remnant of previous community remains) processes. Level 1A disturbances completely destroy communities with no upstream or downstream sources of colonizers, while some component of near surface interstitial or hyporheic flora and fauna survive level 1B disturbances. Recovery has been reported to take from five years to longer than 25 years, when most invading colonists do not have an aerial form. Level 2 disturbances destroy the communities but leave upstream and downstream colonization sources (level 2A) and, sometimes, a hyporheic pool of colonizers (level 2B). Recovery studies have indicated primary succession and faunal structuring patterns (2A) with recovery times of 90–400 days or secondary succession and faunal structuring patterns (2B) with recovery times of 40–250 days. Level 3 disturbances result in reduction in species abundance and diversity along a stream reach; level 4 disturbances result in reduction of abundance and diversity in discrete patches. Both disturbance types lead to secondary succession and secondary faunal organization. Recovery rates can be quite rapid, varying from less than 10 days to 100 or more days. We suggest that island biogeographical models seem appropriate to recovery by secondary processes after level 3 and 4 disturbances, where competition may be an important organizing factor, while models of numerical abundance and resource tracking are probably of better use where community development is by primary succession (levels 1 and 2). Development of predictive recovery models requires research that addresses a number of fundamental questions. These include the role of hydrologic patterns on colonization dynamics, the role of nonaerial colonizers in recovery from level 1 disturbances, and assessment of the impact of changes in the order of invasion by colonizers of varying energetic efficiencies. Finally, we must be able to assemble these data and determine whether information that guides community organization at one level of disturbance can provide insights into colonization dynamics at other levels.     

Integrating forage,wildlife, water,and fish projections with timber projections at the regional level: A case study in southern United States

The impact of timber management and land-use change on forage production, turkey and deer abundance, red-cockaded woodpecker colonies, water yield, and trout abundance was projected as part of a policy study focusing on the southern United States. The multiresource modeling framework used in this study linked extant timber management and land-area policy models with newly developed models for forage, wildlife, fish, and water. Resource production was integrated through a commonly defined land base that could be geographically partitioned according to individual resource needs. Resources were responsive to changes in land use, particularly human-related, and timber management, particularly the harvest of older stands, and the conversion to planted pine.