1,721,117 research outputs found
Agro-ecological indicators of field-farming systems sustainability : 2. Nutrients and pesticides
No full textEvaluation of cropping and farming sustainability can be carried out with direct measurements, simulation models or indicators
the latter have the advantage of requiring a small amount of inputs, being fast to calculate and easy to interpret, allowing
comparisons in space and time, and representing a synthesis of processes in complex systems. In a previous paper,
we proposed a list of indicators related to the use of fossil energy and landscape and soil management. In this paper, we
discuss indicators related to the use of nutrients and pesticides. We selected indicators that can be applied on a field and
farm scale, based on data obtainable from the farmer and/or from existing agricultural databases; we excluded indicators
based on direct measurements.
A nutrient balance is the difference between inputs and outputs of a farm or field (surplus if positive, deficit if negative). Its
advantage is its simplicity, the relatively small data requirement, the identification of different inputs, and its applicability
to different mineral elements. However, nutrient balances do not indicate how much surplus can actually be lost from the
system and in which way. The water quality risk indicator integrates the surplus calculated at field level with simple climatic
and pedological information. We also describe two nitrogen management indicators that have been proposed for arable
crops and grasslands to overcome the limitations of nutrient balances, and the phosphorus management (P) indicator,
which compares the applied P amount with the recommended dose, identifying the risks of spoiling non–renewable resources
or depleting soil reserves.
Compared to nutrients, the use of risk indicators for pesticides is more problematic. As a matter of fact, pesticides show a
greater variety of potential effects on human health and on different ecosystems; consequently, the analysis of their potential
risk requires very complex and varied procedures depending on the environmental compartment considered (ground
water, surface water, air and soil). This has led to the development of several pesticide risk indicators that differ greatly in
terms of variables considered, field of activity, scale of analysis and methodologies utilized (interactive decision–tree, risk
ratio approach, scoring table, fuzzy system). Some indicators use simple algorithms to estimate the risk, others make use of
more complicated models. The simplest and generic indicators require very few data (such as the application rate), but in
general they do not consider the fate on the environment and the distribution of the chemicals. On the contrary, more complex
indicators require the use of predictive models to evaluate potential exposure of non target organisms to different active
ingredients. We present some pesticide risk indicators with different levels of complexity that can be utilized at farm
and field level, in order to obtain a picture of the different approaches available in literature and to point out their values
and limitations
Quantitative inter-specific Chemical Activity Relationships of Pesticides in the Acquatic Environment
No full textInter-species correlations could be a useful tool for predicting toxicity and for establishing sensitivity ratios among species. In this paper, quantitative inter-specific chemical activity relationships (QICAR) for aquatic organisms were developed to verify if such an approach could be utilised for estimating toxicological data when no other information is available. Inter-specific toxicity relationships on fish, Daphnia and algae were performed for pesticides considering a large data set (more than 600 compounds) and grouping the data either on a functional (herbicides, fungicides and insecticides) or chemical class base. Good correlations were found between several fish species and they were improved by excluding, from the data set, highly specific compounds such as organophosphorus insecticides. Relationship between fish (rainbow trout) and Daphnia was significant for the whole data set, but clearly improves if congeneric classes of pesticides are considered. The most significant results were found for azoles (fungicides) and for all data set of pesticides with the exclusion of organophosphorus and carbamate insecticides. As expected, toxicity on algae does not correlate either with fish or with Daphnia on the whole data set, but excluding the classes acting specifically toward one organism (insecticides and several classes of herbicides), good relationships were found. The analysis of the data permits the conclusion that the specificity in the mode action of pesticides is the key parameter for expecting or not inter-specific relationships. By the relative specificity of action of a group of compounds towards two species, the probability of obtaining a QICAR for this group can be derived. In general, compounds acting with the same level of specificity towards two different species, have a higher probability of showing inter-specific relationships and the lower the specificity of the mode of action of the compounds (e.g. narcotics or less inert chemicals), then the stronger are the relationships
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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