The Relative Efficiency of Ranked Set Sampling in Ordinary Least Squares Regression

Ranked set sampling was developed for situations where measurement cost is expensive compared with unit acquisition. This paper presents results of simulations and theory examining the impact of balanced ranked set sampling on the relative efficiencies of the slope and intercept estimators of an ordinary least squares regression. Perfect ranking of either the independent or the dependent variable is assumed throughout. In contradistinction to most of the published ranked set sampling work, it is demonstrated that balanced ranked set sampling offers at most little improvement in the relative efficiencies of the slope estimator at any sample size.     

Mercury deposition through litterfall in an Atlantic forest at Ilha Grande, Southeast Brazil

Atmospheric Hg transfer to the forest soil through litterfall was investigated in a primary rainforest at Ilha Grande (Southeast Brazil) from January to December 1997. Litter mass deposition reached 10.0 t ha⁻¹ y⁻¹, with leaves composing 50–84% of the total litter mass. Concentrations of Hg in the total fallen litter varied from 20 to 244 ng g⁻¹, with higher concentrations during the dry season, between June and August (225 ± 17 ng g⁻¹), and lower concentrations during the rainy season (99 ± 54 ng g⁻¹). This seasonal variability was reflected in the Hg flux through litterfall, which corresponded to a Hg input to the forest floor of 122 μg m⁻² y⁻¹, with average Hg deposition of 16.5 ± 1.5 μg m⁻² month⁻¹ during and just after the dry season (June–September) and 7.0 ± 3.6 μg m⁻² month⁻¹ in the rest of the year. The variability in meteorological conditions (determining atmospheric Hg availability to foliar scavenging) may explain the pulsed pattern of Hg deposition, since litterfall temporal variability was generally unrelated with such deposition, except by a peak in litterfall production in September. Comparisons with regional data on Hg atmospheric deposition show that litterfall promotes Hg deposition at Ilha Grande two to three orders of magnitude higher than open rainfall deposition in non-industrialized areas and approximately two times higher than open rainfall deposition in industrialized areas in Rio de Janeiro State. The observed input suggests that atmospheric Hg transfer through litterfall may explain a larger fraction of the total Hg input to forest soils in Southeast Brazil than those recorded at higher latitudes.     

Predicting non-carcinogenic hazard quotients of heavy metals in pepper (Capsicum annum L.) utilizing electromagnetic waves

• There was significant absorption of heavy metals by the pepper in contaminated soils. • The target hazard quotient (THQ) indices followed the order of Pb>Zn>>Cd » Ni. • Relationships exist between contaminated plants and electromagnetic wave. • PCA and random search can select the main spectra and predict THQ for each element. Given the tendency of heavy metals to accumulate in soil and plants, the purpose of this study was to determine the contamination levels of Cd, Ni, Pb, and Zn on peppers (leaves and fruit) grown in contaminated soils in industrial centers. For this purpose, we measured the uptake of the four heavy metals by peppers grown in the heavy metal contaminated soils throughout the four growth stages: two-leaf, growth, flowering, and fruiting, and calculated various vegetation indices to evaluate the heavy metal contamination potentials. Electromagnetic waves were also applied for analyzing the responses of the target plants to various heavy metals. Based on the relevant spectral bands identified by principal component analysis (PCA) and random search methods, a regression method was then employed to determine the most optimal spectral bands for estimating the target hazard quotient (THQ). The THQ was found to be the highest in the plants contaminated by Pb (THQ= 62) and Zn (THQ= 5.07). The results of PCA and random search indicated that the spectra at the bands of b₅₇₀, b₆₅₀, and b₇₆₀ for Pb, b₄₀₀ and b₁₀₃₀ for Ni, b₄₀₀ and b₈₈₀ for Cd, and b₅₆₀, b₉₁₀, and b₁₀₅₀ for Zn were the most optimal spectra for assessing THQ. Therefore, in future studies, instead of examining the amount of heavy metals in plants by chemical analysis in the laboratory, the responses of the plants to the electromagnetic waves in the identified bands can be readily investigated in the field based on the established correlations.     

Mediation of area and edge effects in forest fragments by adjacent land use

Habitat loss, fragmentation, and degradation have pervasive detrimental effects on tropical forest biodiversity, but the role of the surrounding land use (i.e., matrix) in determining the severity of these impacts remains poorly understood. We surveyed bird species across an interior-edge-matrix gradient to assess the effects of matrix type on biodiversity at 49 different sites with varying levels of landscape fragmentation in the Brazilian Atlantic Forest—a highly threatened biodiversity hotspot. Both area and edge effects were more pronounced in forest patches bordering pasture matrix, whereas patches bordering Eucalyptus plantation maintained compositionally similar bird communities between the edge and the interior and exhibited reduced effects of patch size. These results suggest the type of matrix in which forest fragments are situated can explain a substantial amount of the widely reported variability in biodiversity responses to forest loss and fragmentation.     

Uncertainty in establishing forest reference levels and predicting future forest-based carbon stocks for REDD+

Forest reference levels (FRLs) provide a benchmark for assessing reduced emissions from deforestation and forest degradation (REDD+), and they are central to demonstrate additionality of REDD+. Attaining realistic FRLs, however, is challenging, especially in complex mosaic landscapes. We established FRLs in northern Laos for different reference periods and tested them against actual carbon stock changes. Annual time series of Landsat satellite images were used to capture the subtle changes in carbon stocks in complex landscapes characterized by shifting cultivation. We found that FRLs differ considerably depending on the reference period chosen. Abrupt land-use changes occurred when hybrid maize replaced traditional shifting cultivation and forests, and this invalidated carbon stock trends that would have been predicted had the FRL been projected into the future. We conclude that demonstrating additionality of REDD+ in fast developing areas is difficult and that payment systems rewarding potential emission reductions against hypothetical extrapolation of FRLs are unlikely to be a cost-effective strategy.     

Measuring direct and indirect treatment effects using safety performance intervention functions

Recent traffic safety research has advocated the use of the Full Bayes (FB) approach to conduct controlled before-after safety evaluations. The FB approach was shown to offer both methodological and data advantages. However, there is still a lack of complete understanding of the role that the model parameters play in the formulation of treatment effectiveness. This paper offers a novel approach to compute components related to direct and indirect treatment effects under a linear intervention model for the Safety Performance Function (SPF). The isolation of a component corresponding to the direct treatment effects enables the analyst to assess the effectiveness of the countermeasures apart from local (site-related) environmental factors. Two case studies are used to demonstrate the approach. The first case study is based on the results published from a previous safety evaluation in Iowa and the second uses a new data set from British Columbia based on the Insurance Corporation of British Columbia Road Improvement Program. The various direct and indirect components have yielded valuable insight into the effects of the model parameters on treatment impacts. Moreover, the calculation of the treatment effectiveness indices have been simplified by providing straightforward equations in terms of model parameters for the computation of their components without resorting to additional algorithms. More importantly, the results can have a significant impact on the economic evaluation of safety programs and countermeasures by allowing the calculation of collision modification factors (CMFs) that vary with time.     

Using a Systematic Approach to Select Flagship Species for Bird Conservation

Conservation marketing campaigns that focus on flagship species play a vital role in biological diversity conservation because they raise funds and change people's behavior. However, most flagship species are selected without considering the target audience of the campaign, which can hamper the campaign's effectiveness. To address this problem, we used a systematic and stakeholder‐driven approach to select flagship species for a conservation campaign in the Serra do Urubu in northeastern Brazil. We based our techniques on environmental economic and marketing methods. We used choice experiments to examine the species attributes that drive preference and latent‐class models to segment respondents into groups by preferences and socioeconomic characteristics. We used respondent preferences and information on bird species inhabiting the Serra do Urubu to calculate a flagship species suitability score. We also asked respondents to indicate their favorite species from a set list to enable comparison between methods. The species’ traits that drove audience preference were geographic distribution, population size, visibility, attractiveness, and survival in captivity. However, the importance of these factors differed among groups and groups differed in their views on whether species with small populations and the ability to survive in captivity should be prioritized. The popularity rankings of species differed between approaches, a result that was probably related to the different ways in which the 2 methods measured preference. Our new approach is a transparent and evidence‐based method that can be used to refine the way stakeholders are engaged in the design of conservation marketing campaigns.     

Forest loss,monetary compensation,and delayed re-planting: The effects of unpredictable land tenure in China

Over the past 65 years, forest tenure in China has oscillated unpredictably between private and village property regimes. This policy-induced uncertainty has distorted the harvesting decisions of individuals granted rights to grow trees and has lowered the value of China׳s forest output. We provide an analytical framework for assessing these effects quantitatively. Understanding the consequences of this policy-induced uncertainty is particularly important since China is currently engaged in an ambitious plan to increase its domestic supply of timber. To conduct this analysis, we extend the literature on forestry economics when there is a risk of loss due to forest fire or pests. We (1) take account of the possibility that replanting can only resume after an interval of uncertain length (with immediate replanting as a special Case); (2) investigate the effects of compensation for such losses based only on the net value of the stand of trees at the time of the loss; and (3) compare it to compensation that would leave the wealth and rotation decisions of the farmer unaffected by the presence of uncertainty.     

Addressing onsite sampling in recreation site choice models

Independent experts and politicians have criticized statistical analyses of recreation behavior, which rely upon onsite samples due to their potential for biased inference. The use of onsite sampling usually reflects data or budgetary constraints, but can lead to two primary forms of bias in site choice models. First, the strategy entails sampling site choices rather than sampling individuals—a form of bias called endogenous stratification. Under these conditions, sample choices may not reflect the site choices of the true population. Second, exogenous attributes of the individuals sampled onsite may differ from the attributes of individuals in the population—the most common form in recreation demand is avidity bias. We propose addressing these biases by combining two the existing methods: Weighted Exogenous Stratification Maximum Likelihood estimation and propensity score estimation. We use the National Marine Fisheries Service's Marine Recreational Fishing Statistics Survey to illustrate methods of bias reduction, employing both simulated and empirical applications. We find that propensity score based weights can significantly reduce bias in estimation. Our results indicate that failure to account for these biases can overstate anglers' willingness to pay for improvements in fishing catch, but weighted models exhibit higher variance of parameter estimates and willingness to pay.     

Application of a Random Forest algorithm to predict spatial distribution of the potential yield of Ruditapes philippinarum in the Venice lagoon, Italy

We present a modelling framework that combines machine learning techniques and Geographic Information Systems to support the management of an important aquaculture species, Manila clam (Ruditapes philippinarum). We use the Venice lagoon (Italy), the first site in Europe for the production of R. philippinarum, to illustrate the potential of this modelling approach. To investigate the relationship between the yield of R. philippinarum and a set of environmental factors, we used a Random Forest (RF) algorithm. The RF model was tuned with a large data set (n = 1698) and validated by an independent data set (n = 841). Overall, the model provided good predictions of site-specific yields and the analysis of marginal effect of predictors showed substantial agreement among the modelled responses and available ecological knowledge for R. philippinarum. The most influent environmental factors for yield estimation were percentage of sand in the sediment, salinity, and water depth. Our results agree with findings from other North Adriatic lagoons. The application of the fitted RF model to continuous maps of all the environmental variables allowed estimates of the potential yield for the whole basin. Such a spatial representation enabled site-specific estimates of yield in different farming areas within the lagoon. We present a possible management application of our model by estimating the potential yield under the current farming distribution and comparing it to a proposed re-organization of the farming areas. Our analysis suggests a reduction of total yield is likely to result from the proposed re-organization.