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.     

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.