Estimating preferences for outdoor recreation:: a comparison of continuous and count data demand system frameworks

Continuous and count data demand system models have emerged as attractive alternatives to the discrete choice random utility maximization models (RUMs) that currently dominate the seasonal, multi-site recreation demand literature. This paper compares the frameworks conceptually and investigates their empirical performance with a common data set. Although the two modeling approaches employ substantially different behavioral and econometric assumptions, results from a recreation application based on the 1997 Iowa Wetlands Survey suggest that qualitatively similar policy inferences arise from the competing structures.     

Adjusted two-stage adaptive cluster sampling

An adjusted two-stage sampling procedure is discussed for adaptive cluster sampling where some networks are large and others are small. A two-stage sample is drawn from the large networks and a single-stage sample is drawn from the rest. The simple random sampling (SRS) procedure without replacement is used at the initial stage. An estimator for the population mean along with its properties is discussed.     

3 forest simulation model

The 3 forest simulation model is a process model of tree growth, carbon and nitrogen dynamics in a single-species, even-aged forest stand. It is based on the model. Major changes include the computation of sun angle and radiation as a function of latitude and day of the year, the closed-form integration of canopy production as a function of day and hour, the introduction of tree number, height, and diameter as separate state variables, and different growth strategies, mortalities, and resulting self-thinning as function of crowding competition.The tree/soil system is described by a set of nonlinear ordinary differential equations for the state variables: tree number, base diameter, tree height, wood biomass, nitrogen in wood, leaf mass, fine root mass, fruit biomass, assimilate, carbon and nitrogen in litter, carbon and nitrogen in soil organic matter, and plant-available nitrogen. The model includes explicit formulations of all relevant ecophysiological processes such as: computation of radiation as a function of seasonal time, daytime and cloudiness, light attenuation in the canopy, and canopy photosynthesis as function of latitude, seasonal time, and daytime, respiration of all parts, assimilate allocation, increment formation, nitrogen fixation, mineralization, humification and leaching, forest management (thinning, felling, litter removal, fertilization etc.), temperature effects on respiration and decomposition, and environmental effects (pollution damage to photosynthesis, leaves, and fine roots). Only ecophysiological parameters which can be either directly measured or estimated with reasonable certainty are used. 3 is a generic process model which requires species- and site-specific parametrization. It can be applied to deciduous and coniferous forests under tropical, as well as temperate or boreal conditions.The paper presents a full documentation of the mathematical model as well as representative simulation results for spruce and acacia.     

Phased sampling for soil remediation

In phased sampling, data obtained in one phase is used to design the sampling network for the next phase. GivenN total observations, 1, ...,N phases are possible. Experiments were conducted with one-phase, two-phase, andN-phase design algorithms on surrogate models of sites with contaminated soils. The sampling objective was to identify through interpolation, subunits of the site that required remediation. The cost-effectiveness of alternate methods was compared by using a loss function. More phases are better, but in economic terms, the improvement is marginal. The optimal total number of samples is essentially independent of the number of phases. For two phase designs, 75% of samples in the first phase is near optimal; 20% or less is actually counterproductive.The U.S. Environmental Protection Agency (EPA) through its Office of Research and Development (ORD), partially funded and collaborated in the research described here. It has been subjected to the Agency's peer review and has been approved as an EPA publication. The U.S. Government has a non-exclusive, royalty-free licence in and to any copyright covering this article.     

Paternal care in the European starling,Sturnus vulgaris: nestling provisioning

The extent to which male birds in polygynous species with biparental care assist in nestling feeding often varies considerably between nests of different mating status. Both how much polygynous males assist and how they divide their effort between nests may have a profound effect on the evolution of mating systems. In this study we investigated how males in the facultatively polygynous European starling Sturnus vulgaris invested in their different nests. The amount of male assistance affected the quality of the offspring. Polygynous males invested as much as monogamous males, but divided their effort asymmetrically between nests, predominantly feeding nestlings of first-mated (primary) females. Although females partly compensated for loss of male assistance, total feeding frequency was lower at primary females’ nests than at monogamous females nests. Secondary females received even less assistance with nestling rearing, and the extent to which males assisted decreased with the length of the interval between the hatching of the primary and secondary clutches. These results are contrasted with those from a Belgian populations of starlings with a much more protracted breeding season and thus greater opportunities for males to attract additional mates during the nestling rearing period. The results show that both the “defence of male parental investment model” and the “asynchronous settlement model” have explanatory power, but that their validity depends on the potential length of the breeding season. Received: 21 July 1995/Accepted after revision: 13 July 1996     

treedyn3 forest simulation model

The treedyn3 forest simulation model is a process model of tree growth, carbon and nitrogen dynamics in a single-species, even-aged forest stand. It is based on the treedyn model. Major changes include the computation of sun angle and radiation as a function of latitude and day of the year, the closed-form integration of canopy production as a function of day and hour, the introduction of tree number, height, and diameter as separate state variables, and different growth strategies, mortalities, and resulting self-thinning as function of crowding competition.The tree/soil system is described by a set of nonlinear ordinary differential equations for the state variables: tree number, base diameter, tree height, wood biomass, nitrogen in wood, leaf mass, fine root mass, fruit biomass, assimilate, carbon and nitrogen in litter, carbon and nitrogen in soil organic matter, and plant-available nitrogen. The model includes explicit formulations of all relevant ecophysiological processes such as: computation of radiation as a function of seasonal time, daytime and cloudiness, light attenuation in the canopy, and canopy photosynthesis as function of latitude, seasonal time, and daytime, respiration of all parts, assimilate allocation, increment formation, nitrogen fixation, mineralization, humification and leaching, forest management (thinning, felling, litter removal, fertilization etc.), temperature effects on respiration and decomposition, and environmental effects (pollution damage to photosynthesis, leaves, and fine roots). Only ecophysiological parameters which can be either directly measured or estimated with reasonable certainty are used. treedyn3 is a generic process model which requires species- and site-specific parametrization. It can be applied to deciduous and coniferous forests under tropical, as well as temperate or boreal conditions.The paper presents a full documentation of the mathematical model as well as representative simulation results for spruce and acacia.     

GIS and geostatistics: Essential partners for spatial analysis

Initially, geographical information systems (GIS) concentrated on two issues: automated map making, and facilitating the comparison of data on thematic maps. The first required high quality graphics, vector data models and powerful data bases, the second is based on grid cells that can be manipulated by suites of mathematical operators collectively termed map algebra. Both kinds of GIS are widely available and are taught in many universities and technical colleges. After more than 20 years of development, most standard GIS provide both kinds of functionality and good quality graphic display, but until recently they have not included the methods of statistics and geostatistics as tools for spatial analysis. Recently, standard statistical packages have been linked to GIS for both exploratory data analysis and statistical analysis and hypothesis testing. Standard statistical packages include methods for the analysis of random samples of cases or objects that are not necessarily co-located in space—if the results of statistical analysis display a spatial pattern then that is because the underlying data also share that pattern. Geostatistics addresses the need to make predictions of sampled attributes (i.e., maps) at unsampled locations from sparse, often expensive data. To make up for lack of hard data geostatistics has concentrated on the development of powerful methods based on stochastic theory. Though there have been recent moves to incorporate ancillary data in geostatistical analyses, insufficient attention has been paid to using modern methods of data display for the visualization of results. GIS can serve geostatistics by aiding geo-registration of data, facilitating spatial exploratory data analysis, providing a spatial context for interpolation and conditional simulation, as well as providing easy-to-use and effective tools for data display and visualization. The value of geostatistics for GIS lies in the provision of reliable interpolation methods with known errors, methods of upscaling and generalization, and for supplying multiple realizations of spatial patterns that can be used in environmental modeling. These stochastic methods are improving understanding of how errors in models of spatial processes accrue from errors in data or incompleteness in the structure of the models. New developments in GIS, based on ideas taken from map algebra, cellular automata and image analysis are providing high level programming languages for modeling dynamic processes such as erosion or the development of alluvial fans and deltas. Research has demonstrated that these models need stochastic inputs to yield realistic results. Non-stochastic tools such as fuzzy subsets have been shown to be useful for spatial analysis when probabilistic approaches are inappropriate or impossible. The conclusion is that in spite of differences in history and approach, the linkage of GIS, statistics and geostatistics provides a powerful, and complementary suite of tools for spatial analysis in the agricultural, earth and environmental sciences.     

Rao-Blackwell versions of the Horvitz-Thompson and Hansen-Hurwitz in adaptive cluster sampling

Thompson (1990) introduced the adaptive cluster sampling design and developed two unbiased estimators, the modified Horvitz-Thompson (HT) and Hansen-Hurwitz (HH) estimators, for this sampling design and noticed that these estimators are not a function of the minimal sufficient statistics. He applied the Rao-Blackwell theorem to improve them. Despite having smaller variances, these latter estimators have not received attention because a suitable method or algorithm for computing them was not available. In this paper we obtain closed forms of the Rao-Blackwell versions which can easily be computed. We also show that the variance reduction for the HH estimator is greater than that for the HT estimator using Rao-Blackwell versions. When the condition for extra samples is 0$$ " align="middle" border="0"> , one can expect some Rao-Blackwell improvement in the HH estimator but not in the HT estimator. Two examples are given.     

土壤-植物系统中的碘与碘缺乏病防治

碘是人和动物必需的微量元素之一。碘缺乏将导致甲状腺肿、克汀病等疾病的发生。文章综述了土壤中碘的来源，碘质量分数和形态，影响土壤碘有效性的因素，植物体内碘的质量分数和分布，不同形态的碘对植物生长的影响，碘毒害等方面的研究进展；最后提出防治碘缺乏病的有效措施。     

Female rock shrimp<Emphasis Type="Italic"> Rhynchocinetes typus</Emphasis> mate in rapid succession up a male dominance hierarchy

The dynamics of male-male competition for mates and patterns of female choice depend critically on the social environment. We released newly molted sexually receptive females of the rock shrimp Rhynchocinetes typus in the field and recorded their interactions with males. In the dense aggregations in which these shrimp live, most females were encountered and seized by males within 2 min. Usually, females were first seized by subordinate males, and subsequently taken over by the dominant males. Many females (17 out of 23) had multiple mates during the 10-min observation period, and most of them received spermatophores from multiple males. Males used different mating tactics in accordance with their dominance status: subordinate males often used the sneaking tactic, seizing the female and immediately transferring spermatophores. In contrast, all dominant males used the primary mating tactic; they seized and stimulated the female before transferring spermatophores. Results from previous studies had indicated that females may reduce the fertilization chances of subordinate males by delaying spawning and removing spermatophores. We suggest that this capability in combination with the observed rapid mate succession may enable females to exploit male contest behaviors.Communicated by P. Backwell