Number Of Reference Sites Research Articles

A Multicircle Order Acceptance Strategy for Dynamic Vehicle Routing Problems Considering Customer Choice of Last-Mile Delivery Modes and Time Slots

A multicircle order acceptance strategy was proposed to decide whether to accept customer requests for specific last-mile delivery modes (including attended home or reception box delivery) and time slots. The strategy was composed of initializing acceptable time slot allocations, reallocating acceptable time slots, matching reference sites, and assessing time slot deviations. A strategy-oriented insertion algorithm for dynamic vehicle routing problems with hard time windows was constructed, thereby showing the proposed strategy achieves a better balance between revenue and distance than the “first come and first served” strategy. Always accepting global optimization result is not significantly better than adopting the result conditionally or based on simulated annealing theory. The distance and revenue gradually increase with the number of reference sites, while revenue/distance ratio decreases. The vehicles are available to serve more attended home delivery orders with a gradual increase in time slot interval, thereby leading to an increase of AHD and total revenue.

Bioassessment of freshwater ecosystems using the Reference Condition Approach: comparing established and new methods with common data sets

AbstractAlthough used in many jurisdictions around the world, analytical approaches of the Reference Condition Approach (RCA) to bioassessment of freshwater ecosystems have evolved quite slowly over the past 2 decades. For this special series of papers in Freshwater Science, researchers analyzed 3 data sets that included both benthic macroinvertebrate and environmental data from a number of reference sites. Australian Capital Territory (ACT) reference sites (ntotal = 107) were wadeable streams in the upper Murrumbidgee River catchment, Australian Capital Territory, Australia. Yukon Territory (YT) reference sites were wadeable streams (ntotal = 158) in the Yukon Territory, Canada, part of the Yukon River basin. Great Lakes (GL) sites (ntotal = 164) were all nearshore (<20 m) lentic sites in the North American Great Lakes. For each data set, sites were divided into model-building (training) and model-testing (validation) groups. Each validation site was further subjected to 3 levels of simulated degradation...

Using biological data from field studies with multiple reference sites as a basis for environmental management: The risks for false positives and false negatives

Field surveys of biological responses can provide valuable information about environmental status and anthropogenic stress. However, it is quite usual for biological variables to differ between sites or change between two periods of time also in the absence of an impact. This means that there is an obvious risk that natural variation will be interpreted as environmental impact, or that relevant effects will be missed due to insufficient statistical power. Furthermore, statistical methods tend to focus on the risks for Type-I error, i.e. false positives. For environmental management, the risk for false negatives is (at least) equally important. The aim of the present study was to investigate how the probabilities for false positives and negatives are affected by experimental set up (number of reference sites and samples per site), decision criteria (statistical method and α-level) and effect size. A model was constructed to simulate data from multiple reference sites, a negative control and a positive control. The negative control was taken from the same distribution as the reference sites and the positive control was just outside the normal range. Using the model, the probabilities to get false positives and false negatives were calculated when a conventional statistical test, based on a null hypothesis of no difference, was used along with alternative tests that were based on the normal range of natural variation. Here, it is tested if an investigated site is significantly inside (equivalence test) and significantly outside (interval test) the normal range. Furthermore, it was tested how the risks for false positives and false negatives are affected by changes in α-level and effect size. The results of the present study show that the strategy that best balances the risks between false positives and false negatives is to use the equivalence test. Besides tests with tabulated p-values, estimates generated using a bootstrap routine were included in the present study. The simulations showed that the probability for management errors was smaller for the bootstrap compared to the traditional test and the interval test.

Spatial and annual variation to define the normal range of biological endpoints: An example with biomarkers in perch

A signal from a biological endpoint can be considered evidence of environmental impact only if it is known that similar signals are unlikely to occur naturally. Using multiple reference sites, the normal range can be estimated. This can be defined as the span that includes 95% of the reference sites. If an investigated site is outside this range, it is interpreted as evidence of impact. The choice of reference sites is thus important for the outcome of the study. Here, biomarker levels in perch (Perca fluviatilis) at a potentially impacted site were compared to different types of reference data. The potentially impacted site was located close to a densely populated area. Four reference sites were located in relatively undisturbed areas on the Swedish Baltic coast. Furthermore, historical data from one of the reference sites were included. The present study showed that multiple reference sites are needed to avoid the risk of interpreting natural variation as impact. The number of reference sites needed depends on the desired level of statistical power. An alternative to multiple reference sites may be to use historical data to estimate the natural variation. However, historical data can include temporal variation due to factors that may not be relevant for the hypothesis that is tested, e.g., climatic variation or changed background levels of pollution.

Theoretical predictions of observed to expected ratios in RIVPACS-type predictive model assessments of stream biological condition

AbstractRiver InVertebrate Prediction And Classification System (RIVPACS)-type predictive models assess the biological conditions of streams by comparing observed assemblage composition (O) with an expected assemblage composition derived from reference site observations (E). The ratio of the 2 values (O/E) can be interpreted as a measure of taxonomic completeness. Values of O/E that are near 1 at a test site suggest that the site is comparable to reference sites, whereas values that differ substantially from 1 suggest that the site is degraded. I analyzed the computations involved in estimating E mathematically. The analysis reveals that many predictive models produce values of O/E that are systematically <1, even when the models are applied to sites that have the same average assemblage composition as reference sites. The amount by which O/E values are <1 depends upon the number of reference sites used to build the model, the manner in which these reference sites are distributed among discrete clusters, ...

U.S. CONTRIBUTIONS TO THE CEOP

Abstract The Coordinated Enhanced Observing Period (CEOP) is an international project that was first proposed by the Global Energy and Water Cycle Experiment (GEWEX) in 1997 and was formally launched in 2001. Since that time it has been adopted by the World Climate Research Programme (WCRP), which views it as an essential part of its strategy for developing global datasets to evaluate global climate models, and by the Integrated Global Observing Strategy Partnership (IGOS-P), which views it as the first element of its global water cycle theme. The United States has been an active partner in all phases of CEOP. In particular, the United States has taken the lead in contributing data from a number of reference sites, providing data processing, and archiving capabilities and related research activities through the GEWEX Americas Prediction Project (GAPP). Other U.S. programs and agencies are providing components including model and data assimilation output, satellite data, and other services. The U.S. scienc...

Rapid zonation of abrupt mass movement hazard: Part I. General principles

Hazards caused by mass movement cost many human lives and cause severe damage to property. Accurate zonation of such hazards provides an important tool for preventive measures. Previous approaches for mass movement hazard zonation are costly because they require large amounts of data, time and labor, and are only applicable to specific local areas. In this paper, a Rapid Zonation of Abrupt Mass-movement Hazard (RZAMH), applicable to large regions, is proposed. It involves the selection of appropriate zonation principles, routes, units, and indexes that can be used for the classification of reference groups, identification of matching groups of test sites, evaluation of blank test sites, and coalescence of sub-regions into specified zonation areas. The K-means clustering method is used in the classification processes. The applicability of the RZAMH approach to a large area implies that the number of reference sites required to build the reference groups is not of primary importance as long as the reference sites are representative. Therefore, for large areas, the RZAMH approach would be more economical than other conventional methods. The RZAMH approach is probably applicable to all abrupt mass movement hazards including rock falls, landslides, and debris flows.

ASSESS INTERTIDAL IMPACTS: LESSONS LEARNED FROM 11 YEARS OF MONITORING IN PRINCE WILLIAM SOUND1

ABSTRACT “How many samples do we need?” and “Where should we collect them?” are questions common to most field monitoring programs. They are especially compelling when an oil spill impinges on a coastline and an intertidal monitoring program must be rapidly implemented to assess impacts. Moreover, these initial sampling decisions profoundly affect the ultimate validity of the assessment study. While it is important to avoid squandering limited resources by oversampling, an undersized study is equally wasteful if it cannot reliably discern significant impacts and produce useful results. All else being equal, the power to detect change in an ecosystem is dictated by its inherent variability. Variability estimates were computed for a variety of intertidal assemblages using data collected within Prince William Sound over eleven years, following the Exxon Valdez oil spill. The sample-size recommendations that emerge from these power analyses demonstrate that spill and cleanup impacts to most intertidal taxa can be reliably detected using four to six replicate samples collected at three or more treatment sites, and at an equivalent number of reference sites. They also demonstrate that collecting more than eight replicate samples within each site does little to increase the power to detect differences in mean populations. Analogously, “parallelism” tests on multi-year data provide a reliable means of quantifying long-term recovery in intertidal populations following an oil spill. Parallelism tests examine temporal trends in mean abundance at impacted sites relative to reference sites. However, the ability to detect major recolonization events with parallelism tests varies widely depending on the taxa being tested. For example, the marked recolonization in Fucus and epifaunal invertebrates that was experienced four years after the Exxon Valdez spill could have been detected by sampling at only two reference and two impact sites. In contrast, infaunal populations exhibit greater variability, making detection of nonparallel trends difficult without sampling at least six reference and six impacted sites.