Rethinking assessment of success of mitigation strategies for elephant-induced crop damage

Crop damage is the most common impact of negative interactions between people and elephants and poses a significant threat to rural livelihoods and conservation efforts. Numerous approaches to mitigate and prevent crop damage have been implemented throughout Africa and Asia. Despite the documented high efficacy of many approaches, losses remain common, and in many areas, damage is intensifying. We examined the literature on effectiveness of crop-damage-mitigation strategies and identified key gaps in evaluations. We determined there is a need to better understand existing solutions within affected communities and to extend evaluations of effectiveness beyond measurement of efficacy to include rates of and barriers to adoption. We devised a conceptual framework for evaluating effectiveness that incorporates the need for increased emphasis on adoption and can be used to inform the design of future crop-damage mitigation assessments for elephants and conflict species more widely. The ability to prevent crop loss in practice is affected by both the efficacy of a given approach and rates of uptake among target users. We identified the primary factors that influence uptake as local attitudes, sustainability, and scalability and examined each of these factors in detail. We argue that even moderately efficacious interventions may make significant progress in preventing damage if widely employed and recommend that wherever possible scientists and practitioners engage with communities to build on and strengthen existing solutions and expertise. When new approaches are required, they should align with local attitudes and fit within limitations on labor, financial requirements, and technical capacity.     

Sampling strategies in the assessment of long‐term exposures to toxic substances in air

The decision to mitigate exposures from vapor intrusion (VI) is typically based on limited data from 24‐hour air samples. It is well documented that these data do not accurately represent long‐term average exposures linked to adverse health effects. Limited decision guidance is currently available to determine the most appropriate sampling strategy, considering the cost of sampling alternatives along with the economic consequences of exposure‐related health effects. We present a decision model that introduces economic and statistical considerations in evaluating alternative VI sampling methods. The model characterizes the best sampling method by factoring economic and health consequences of exposure, the variability of exposure, the cost of sampling and mitigation, and the likelihood of false‐negatives and false‐positives. Decision‐makers can use results to select the sample size that maximizes net benefit. Conceptual and mathematical models are presented linking biological, statistical, and economic considerations to assess the cost and effectiveness of different sampling strategies. The model relates an average exposure concentration, determined statistically, to abatement costs and to the monetary value of health deterioration. The value of the information provided by different strategies is calculated and used to select the optimum sampling method. Simulations show that longer‐term sampling methods tend to be more accurate and cost‐effective than short‐term samples. The ideal sampling strategy shows significant seasonal variation (it is typically optimal to use longer samples in the winter) and also varies significantly with the stringency of regulatory standards. Longer‐term sample collection provides a more accurate representation of average VI exposure and reduces the likelihood of type I and type II errors. This reduces expected costs of mitigation and exposure (e.g., health consequences, legal and regulatory penalties), which in some cases can be quite significant. The model herein shows how these savings are balanced against the additional costs of longer‐term sampling.     

Using fuzzy set theory to address the uncertainty of susceptibility to drought

This paper presents the technical aspects of a new methodology for assessing the susceptibility of society to drought. The methodology consists of a combination of inference modelling and fuzzy logic applications. Four steps are followed: (1) model input variables are selected—these variables reflect the main factors influencing susceptibility in a social group, population or region, (2) fuzzification—the uncertainties of the input variables are made explicit by representing them as ‘fuzzy membership functions’, (3) inference modelling—the input variables are used to construct a model made up of linguistic rules, and (4) defuzzification—results from the model in linguistic form are translated into numerical form, also through the use of fuzzy membership functions. The disadvantages and advantages of this methodology became apparent when it was applied to the assessment of susceptibility from three disciplinary perspectives: Disadvantages include the difficulty in validating results and the subjectivity involved with specifying fuzzy membership functions and the rules of the inference model. Advantages of the methodology are its transparency, because all model assumptions have to be made explicit in the form of inference rules; its flexibility, in that informal and expert knowledge can be incorporated through ‘fuzzy membership functions’ and through the rules in the inference model; and its versatility, since numerical data can be converted to linguistic statements and vice versa through the procedures of ‘fuzzification’ and ‘defuzzification’.     

Municipal anaerobic digesters for codigestion, energy recovery, and greenhouse gas reductions.

Codigestion of five wastes and municipal wastewater sludge was evaluated using full-scale testing. Synergistic, antagonistic, and neutral outcomes were observed depending on codigestate identity and concentration, highlighting the value of careful blending. Yeast waste resulted in notable synergism, increasing biogas production by over 50%, whereas aircraft deicing waste resulted in antagonism at high loadings and neutral outcomes at lower loadings. Restaurant waste codigestion resulted in neutral outcomes. The synergisim with yeast codigestates may have resulted from trace nutrients (i.e., iron, nickel, and cobalt) in the wastes that increased microbiological activity. Antagonist outcomes with deicing waste may have been the result of organic overload or inhibitory deicer constituents. Codigestion of wastes at the feed rates investigated was estimated to produce 0.50 ML/d of methane having an energy equivalent of 17 500 MJ/d. This was estimated to reduce net carbon dioxide emissions by 560 tonnes/y.     

A comparison of different lysis buffers to assess allele dropout from single cells for preimplantation genetic diagnosis

Single cell polymerase chain reaction (PCR) for preimplantation genetic diagnosis (PGD) requires high efficiency and accuracy. Allele dropout (ADO), the random amplification failure of one of the two parental alleles, remains the most significant problem in PCR-based PGD testing since it can result in serious misdiagnosis for compound heterozygous or autosomal dominant conditions. A number of different strategies (including the use of lysis buffers to break down the cell and make the DNA accessible) have been employed to combat ADO with varying degrees of success, yet there is still no consensus among PGD centres over which lysis buffer should be used (ESHRE PGD Consortium, 1999 ). To address this issue, PCR amplification of three genes (CFTR, LAMA3 and PKP1) at different chromosomal loci was investigated. Single lymphocytes from individuals heterozygous for mutations within each of the three genes were collected and lysed in either alkaline lysis buffer (ALB) or proteinase K/SDS lysis buffer (PK). PCR amplification efficiencies were comparable between alkaline lysis and proteinase K lysis for PCR products spanning each of the three mutated loci (ΔF508 in CFTR 90% vs 88%; R650X in LAMA3 82% vs 78%; and Y71X in PKP1 91% vs 87%). While there was no appreciable difference between ADO rates between the two lysis buffers for the LAMA3 PCR product (25% vs 26%), there were significant differences in ADO rates between ALB and PK for the CFTR PCR product (0% vs 23%) and the PKP1 PCR product (8% vs 56%). Based on these results, we are currently using ALB in preference to PK/SDS buffer for the lysis of cells in clinical PGD. Copyright © 2001 John Wiley & Sons, Ltd.     

Optimal range of plug-in electric vehicles in Beijing and Shanghai

Both China’s national subsidy policies for plug-in electric vehicles (PEVs) purchasers and passenger cars corporate average fuel consumption and new vehicle credit regulation (dual-credit policy) favor long-range 300+ km battery electric vehicles (BEVs) and 80+ km plug-in hybrid electric vehicles (PHEVs). However, these electric vehicles tend to have lower energy efficiency and higher purchase and operation costs. Vehicle with larger batteries can also be less equitable because the subsidies are often provided to more expensive vehicles and wealthier owners. This study takes advantage of a novel dataset of daily driving data from 39,854 conventional gasoline vehicles in Beijing and 4999 PHEVs in Shanghai to determine the optimal range of BEVs and PHEVs within their respective cities. We simulate a model to explore ranges with which PEVs emit less GHGs than that of a baseline hybrid and conventional gasoline vehicle while ensuring that all daily travel demands are met. Our findings indicate that in both cities, the optimal ranges to balance cost and travel demand for BEVs are 350 km or less and for PHEVs are 60 km or less in Beijing and 80 km or less in Shanghai. We also find that to minimize carbon dioxide (CO₂) emissions, the ranges are even lower 10 km in Beijing and 30 km in Shanghai. Our study suggests that instead of encouraging long-range PEVs, governments should subsidize PEV models with shorter ranges. Parallel efforts should also be made to both increase renewable energy over fossil fuels and expand charging facilities. Although individual mobility demand varies, the government could reduce occasional long-distance driving by subsidizing alternative transportation choices. Providing week-long driving trials to consumers before their purchases may help decrease the demand of very long range PEVs by alleviating the range anxiety through a learning process.

     

Guppies and the TIT FOR TAT strategy: preference based on past interaction

Summary The evolution of cooperation requires either (a) nonrandom interactions, such that cooperators preferentially interact with other cooperators, or (b) conditional behaviors, such that individuals act cooperatively primarily towards other cooperators. Although these conditions can be met without assuming sophisticated animal cognition, they are more likely to be met if animals can remember individuals with whom they have interacted, associate past interactions with these individuals, and base future behavior on this information. Here we show that guppies (Poecilia reticulata), in the context of predator inspection behavior, can identify and remember (for at least 4 h) the more cooperative among two conspecifics and subsequently choose to be near these individuals in future encounters. Offprint requests to: L.A. Dugatkin     

Woodstove emission measurement methods: Comparison and emission factors update

On February 26, 1988, the U.S. Environmental Protection Agency promulgated Standards of Performance for residential wood heaters, or woodstoves. Over the past several years, a number of field studies have been undertaken to determine the actual level of emission reduction achieved by new technology woodstoves in everyday use. These studies have required the development and use of particulate and gaseous emission sampling equipment compatible with operation in private houses. Since woodstoves are tested for certification in the laboratory using EPA Methods 5G and 5H, it is of substantial interest to determine the correlation between these regulatory methods and the in-house equipment. Two in-house sampling systems have been used most widely. One is an intermittent, pump-driven particulate sampler which collects particulate and condensable organics on a filter and organic adsorbent resin. Oxygen concentration is measured by a sensor in the sample line. The sampler is controlled by a data logger which also records other parameters of interest. The second system uses an evacuated cylinder as the motive force. Particulate and condensable organics are collected in a condenser and dual filter. The sampler operates continuously whenever the stack temperature is above the set point. Average stack gas concentrations are measured from the evacuated cylinder at the conclusion of the sampling period. Both samplers were designed to operate unattended for 1-week periods. A large number of tests have been run comparing Methods 5G and 5H to both of the field samplers. This paper presents these comparison data and determines the relationships between laboratory certification sampling methods and field samplers.