A Bark Thickness Model for White Spruce in Alaska Northern Forests

Here we developed a simple linear model to estimate white spruce bark thickness in the northern forests of Alaska. Data were collected from six areas throughout interior and southcentral Alaska. Geographic variation of bark thickness was tested between the Alaska statewide model and for each geographic area. The results show that the Alaska statewide model is accurate, simple, and robust, and has no practical geographic variation over the six areas. The model provides accurate estimates of the bark thickness for white spruce trees in Alaska for a wide array of future studies, and it is in demand by landowners and forest managers to support their management decisions.We are obligated to Carol E. Lewis and Edmond C. Packee for supporting this bark thickness research. This research was also supported in part by the United States Department of Agriculture, McIntire-Stennis Act Fund ALK-03-12, and by the School of Natural Resources and Agricultural Sciences, University of Alaska Fairbanks.We thank the associate editor, Han Chen, and an anonymous reviewer for their helpful comments

Total and Merchantable Volume of White Spruce in Alaska

White spruce (Picea glauca [Moench] Voss) is a valuable commercial species found in interior and southcentral Alaska. Numerous regional and local volume tables or equations exist; however, no statewide model exists or has been tested for accuracy. There is a demand for an accurate model to determine the cubic-foot volume of white spruce trees in Alaska. Multiple models were developed for white spruce to estimate total and merchantable cubic-foot volume to a 2-, 4-, and 6-in. top. These multiple-entry (diameter and height) models were developed for both inside and outside bark volume from a 6-in. stump. The models were tested on a regional basis at various geographic locations and were shown to be highly accurate. The Alaska models chosen have R2 at or near 0.99 and mean square error from 0 to 0.16 for all models. These models are shown to be superior to other white spruce models in Alaska.This research was supported in part by the US Department of Agriculture, McIntire-Stennis Act Fund ALK-03-12, and by the School of Natural Resources and Agricultural Sciences, University of Alaska Fairbanks

MP 2012-01

In 1994 the University of Alaska Fairbanks, School of Natural Resources and Agricultural Sciences, Agricultural and Forestry Experiment Station began a project to establish permanent sample plots (PSP) throughout the forests of northern and southcentral Alaska. Objectives of the project are to establish and maintain a system of PSPs to monitor forest growth, yield, forest health, and ecological conditions/change (Malone et al., 2009). To date, 603 PSPs have been established on 201 sites throughout interior and southcentral Alaska. The PSPs are square and 0.1 acre in size and in clusters of three. PSPs are remeasured at a five-year interval. The number of plot remeasurements after establishment ranges from one to three times. A large amount of data is collected at each site at time of establishment and at subsequent remeasurements. Four databases contain all the data: tree measurement and characteristics, site description, regeneration, and vegetation data. Vegetation data collected on the 0.1 acre PSPs includes species (trees shrub, herb, grass, and non-vascular plants) and cover, an estimate of the amount of the plot covered by the crown of each species (cover class) (Daubenmire, 1959). The vegetation database can be used by land managers and researchers to study species diversity and forest succession in addition to long-term monitoring of forest health. The species listed in Appendix 1 and in the vegetation database are presented by categories: tree, shrub, herb, grass, rush, sedge, fern, club moss, lichen, moss, and liverwort

COST-EFFECTIVE TECHNIQUES FOR CONTINUOUS INTEGRATION TESTING

Continuous integration (CI) development environments allow software engineers to frequently integrate and test their code. While CI environments provide advantages, they also utilize non-trivial amounts of time and resources. To address this issue, researchers have adapted techniques for test case prioritization (TCP) and regression test selection (RTS) to CI environments. To date, current TCP techniques under CI environments have operated on test suites, and have not achieved substantial improvements. In this thesis, we use a lightweight approach based on test suite failure and execution history, and “continuously” prioritizes commits that are waiting for execution in response to the arrival of each new commit and the completion of each previously commit scheduled for testing. We conduct an empirical study on three datasets, and the result shows that, after prioritization, our technique can effectively detect failing commits earlier. To date, current RTS techniques under CI environment is based on two windows in terms of time. But this technique fails to consider the arrival rate of test suites and only takes the results of test suites execution history into account. In this thesis, we present a Count-Based RTS technique, which is based on the test suite failures and execution history by utilizing two window sizes in terms of number of test suites, and a Transition-Based RTS technique, which adds the test suites’ “pass to malfunction” transitions for selection prediction in addition to the two window sizes. We again conduct an empirical study on three datasets, and the results show that, after selection, Transition-Based technique detects more malfunctions and more “pass to malfunction” transitions than the existing techniques. Adviser: Gregg Rothermel, Sebastian Elbau

Matrix models for size-structured populations: Unrealistic fast growth or simply diffusion?

Matrix population models are widely used to study population dynamics but have been criticized because their outputs are sensitive to the dimension of the matrix (or, equivalently, to the class width). This sensitivity is concerning for the population growth rate (l) because this is an intrinsic characteristic of the population that should not depend on the model specification. It has been suggested that the sensitivity of l to matrix dimension was linked to the existence of fast pathways (i.e. the fraction of individuals that systematically move up a class), whose proportion increases when class width increases. We showed that for matrix population models with growth transition only from class i to class iz1, l was independent of the class width when the mortality and the recruitment rates were constant, irrespective of the growth rate. We also showed that if there were indeed fast pathways, there were also in about the same proportion slow pathways (i.e. the fraction of individuals that systematically remained in the same class), and that they jointly act as a diffusion process (where diffusion here is the movement in size of an individual whose size increments are random according to a normal distribution with mean zero). For 53 tree species from a tropical rain forest in the Central African Republic, the diffusion resulting from common matrix dimensions was much stronger than would be realistic. Yet, the sensitivity of l to matrix dimension for a class width in the range 1-10 cm was small, much smaller than the sampling uncertainty on the value of l. Moreover, l could either increase or decrease when class width increased depending on the species. Overall, even if the class width should be kept small enough to limit diffusion, it had little impact on the estimate of l for tree species. (Résumé d'auteur

Multi-Plant Production and Transportation Planning Based on Data Envelopment Analysis

This paper proposes a methodology for developing a coordinated aggregate production plan for manufacturers producing multiple products at multiple plants simultaneously, in a centralized environment via data envelopment analysis (DEA). Based on demand forecast of the planning horizon, the central decision maker (DM) specifies the optimal combination of input resources required by the optimal output targets for each plant to keep the supply and demand in balance, and the accompanying transportation trips and volumes among distribution centers (DCs) or warehouse facilities. In this paper, we focus on an integrated production-transportation problem since production and transportation are two fundamental ingredients in the whole operation chain. We deal with multiple products manufactured in multiple plants.The proposed mixed integer DEA models minimize both production costs and transportation costs. The capacity constraint for each plant is enforced by using the production possibility set theory. Finally, we validate our models by a numerical example and sensitivity analysis

The Impact of Perceived Risk on Customers’ Intention to Use -- An Empirical Analysis of DiDi Car-Sharing Services

With the development of internet and modern technologies, sharing economy grows quickly and attracts more attention. Sharing platforms have more uncertainty and perceived risk, which influences the customers’ intention to use. In this paper, we take DiDi, a ridesharing platform in China as a case to study. We take the perspective of customers and investigate the implications of perceived risk and trust on customers’ intention to use. We conceptualized perceived risk as a multi dimension construct and differentiate trust on DiDi and trust on drivers. The study employs survey data (n = 365) and structural equation modeling (SEM). Our results provide empirical evidence for the relationship between perceived risk, trust and customers’ intention to use. This research has both significant theoretical and practical implications. It applies the theory of perceived risk and trust in Chinses situation. In practice, the ridesharing platform need to pay more attention to the security of customers, thus more speculation and control on drivers are expected

Tree species richness enhances stand productivity while stand structure can have opposite effects, based on forest inventory data from Germany and the United States of America

Background: In recent studies, mixed forests were found to be more productive than monocultures with everything else remaining the same. Methods: To find out if this productivity is caused by tree species richness, by a more heterogeneous stand structure or both, we analyzed the effects of forest structure and tree species richness on stand productivity, based on inventory data of temperate forests in the United States of America and Germany. Results: Having accounted for effects such as tree size and stand density, we found that: (I) tree species richness increased stand productivity in both countries while the effect of tree size heterogeneity on productivity was negative in Germany but positive in the USA; (II) productivity was highest at sites with an intermediate amount of precipitation; and (III) growth limitations due water scarcity or low temperature may enhance structural heterogeneity. Conclusions: In the context of forest ecosystem goods and services, as well as future sustainable forest resource management, the associated implications would be: Tree species richness is vital for maintaining forest productivity. As an optimum amount of precipitation is accompanied by the highest productivity, changes in climatic conditions should be considered when planning. Resource limitations enhance structural heterogeneity, which in turn can have positive or negative effects on stand productivity. Furthermore, we discuss the difficulties encountered when analyzing different national forest inventories and large data sets

Evaluating the Impacts of Parking App Services on Travellers\u27 Choice Behaviour and Traffic Dynamics

As the products of intelligent transportation systems, parking apps have become convenient platforms for implementing parking policies, which can be provided as parking app services. This paper proposes a traffic simulation model for evaluating the impacts of parking app services on the travellers’ choice behaviour and traffic dynamics. Travellers are assumed to use three types of parking app services: the provision of information on real-time parking lot occupancies, parking reservation, and the display of dynamic parking fees. The behaviour of travellers, such as travellers’ mode choices, departure time choices, and learning behaviour, are considered in this model. Numerical experiments show that providing information on real-time parking lot occupancies can be helpful in reducing the use ratio of commercial parking lots, but the effect will ultimately be smoothed during the evolution of traffic dynamics. Moreover, parking reservation is an effective way to reduce travel costs and encourage travellers to choose park-and-ride. Furthermore, dynamic parking fees usually lead to the oscillation of traffic dynamics and travellers’ choices, in addition to an increase in travel costs. This model is a useful tool for analysing the impacts of other parking management policies that can be implemented as parking app services and can be a reference for evaluating the impacts of other parking polices.</p