Performance of Two Fruit Fly (Diptera: Tephritidae) Pupal Parasitoids (Coptera haywardi [Hymenoptera: Diapriidae] and Pachycrepoideus vindemiae [Hymenoptera: Pteromalidae]) under Different Environmental Soil Conditions

We evaluated the performance of Coptera haywardi (Ogloblin) (Diapriidae) and Pachycrepoideus vindemiae (Rondani) (Pteromalidae), both hymenopteran pupal parasitoids of Anastrepha spp. (Diptera: Tephritidae). Performance was studied by manipulating the following environmental conditions in the laboratory: (1) soil type, (2) soil moisture content, (3) soil compaction, and (4) depth at which pupae were buried in the soil. There were two experiments: in the first, exposure time of pupae was held constant and in the second, it varied. In the first experiment, C. haywardi was significantly more effective than P. vindemiae in parasitizing fly pupae. With exposure time held constant (36 h), only soil type and pupal burial depth were significantly related to parasitism rates. While P. vindemiae only parasitized pupae located on the soil surface, C. haywardi attacked pupae that were buried up to 5 cm deep, performing better in clayey than in loamy soil. In the second experiment, exposure time (24, 36, 48, and 72 h) had no significant effect on parasitism rates, but soil type did. P. vindemiae again only attacked pupae on the soil surface while C. haywardi was also able to parasitize pupae that were buried up to 5 cm deep. We conclude that C. haywardi represents a viable candidate to replace the environmentally unfriendly P. vindemiae in augmentative biological control programs against fruit flies.     

Phytochemical Characterization of Cannabis sativa L. Roots from Northeastern Brazil

This article describes the phytochemical study of Cannabis sativa roots from northeastern Brazil. The dried plant material was pulverized and subjected to exhaustive maceration with ethanol at room temperature, obtaining the crude ethanolic extract (Cs-EEBR). The volatile compounds were analyzed by gas chromatography coupled with mass spectrometry (GC/MS), which allowed to identify 22 compounds by comparing the linear retention index (LRI), the similarity index (SI) and the fragmentation pattern of the constituents with the literature. By this technique the major compounds identified were: friedelan-3-one and β-sitosterol. In addition, two fractions were obtained from Cs-EEBR by classical column chromatography and preparative thin layer chromatography. These fractions were analyzed by NMR and IR and together with the mass spectrometry data allowed to identify the compounds: epifriedelanol, friedelan-3-one, β-sitosterol and stigmasterol. The study contributed to the phytochemical knowledge of Cannabis sativa, specifically the roots, as there are few reports on the chemical constituents of this part of the plant.     

Focus: Bioethics: Targeting Representation: Interpreting Calls for Diversity in Precision Medicine Research

Scientists have identified a “diversity gap” in genetic samples and health data, which have been drawn predominantly from individuals of European ancestry, as posing an existential threat to the promise of precision medicine. Inadequate inclusion as articulated by scientists, policymakers, and ethicists has prompted large-scale initiatives aimed at recruiting populations historically underrepresented in biomedical research. Despite explicit calls to increase diversity, the meaning of diversity – which dimensions matter for what outcomes and why – remain strikingly imprecise. Drawing on our document review and qualitative data from observations and interviews of funders and research teams involved in five precision medicine research (PMR) projects, we note that calls for increasing diversity often focus on “representation” as the goal of recruitment. The language of representation is used flexibly to refer to two objectives: achieving sufficient genetic variation across populations and including historically disenfranchised groups in research. We argue that these dual understandings of representation are more than rhetorical slippage, but rather allow for the contemporary collection of samples and data from marginalized populations to stand in as correcting historical exclusion of social groups towards addressing health inequity. We trace the unresolved historical debates over how and to what extent researchers should procure diversity in PMR and how they contributed to ongoing uncertainty about what axes of diversity matter and why. We argue that ambiguity in the meaning of representation at the outset of a study contributes to a lack of clear conceptualization of diversity downstream throughout subsequent phases of the study.     

Synthesis of 2-ethylhexyl oleate catalyzed by Candida antarctica lipase immobilized on a magnetic polymer support in continuous flow

Bioprocess and Biosystems Engineering - This study investigated the synthesis of 2-ethylhexyl oleate catalyzed by Candida antarctica lipase immobilized on magnetic poly(styrene-co-divinylbenzene)...     

A novel cellular automata approach: seed input/output of the alien species Leucaena leucocephala in the soil and the effects of climate changes

The potential impact of the soil seed bank of a given species and subsequent population persistence will depend on the robustness of the seeds against depletion. Invasiveness is frequently linked to this behavior and successful control of invasive species depends on reducing the size of their seed banks. We propose a hybrid model that simulates the seed bank dynamics in association with their physical dormancy (PD) based on experimental data on seed bank depletion of a Leucaena leucocephala population during the dispersal phase. The hybrid model uses cellular automata (CA) and Monte Carlo techniques. The sensitivity analysis revealed that the model delivers reproducible and reliable results. Then, we discuss the ability of the hybrid model to predict the effect of seasonal climate change. A 2.0 °C increase in temperature was enough to cause a considerable impact in the seed depletion curve, and after 1 year, ~?75% of the seeds had already disappeared from the seed bank. The proposed hybrid CA model can be used to study soil-stored seed banks with physical dormancy, and could be applied to other Fabaceae species with similar seed traits. We believe that this computational model contributes to a better understanding of seed bank dynamics and will aid in the control of invasive species and for testing different scenarios to reduce or eliminate seed banks that have already been formed.

     

Revisiting the dimensionality of biological diversity

Biodiversity can be represented by different dimensions. While many diversity metrics try to capture the variation of these dimensions they also lead to a ‘fragmentation’ of the concept of biodiversity itself. Developing a unified measure that integrates all the dimensions of biodiversity is a theoretical solution for this problem, however, it remains operationally impossible. Alternatively, understanding which dimensions better represent the biodiversity of a set of communities can be a reliable way to integrate the different diversity metrics. Therefore, to achieve a holistic understand of biological diversity, we explore the concept of dimensionality. We define dimensionality of diversity as the number of complementary components of biodiversity, represented by diversity metrics, needed to describe biodiversity in an unambiguously and effective way. We provide a solution that joins two components of dimensionality – correlation and the variation – operationalized through two metrics, respectively: evenness of eigenvalues (EE) and importance values (IV). Through simulation we show that considering EE and IV together can provide information that is neglected when only EE is considered. We demonstrate how to apply this framework by investigating the dimensionality of South American small mammal communities. Our example evidenced that, for some representations of biological diversity, more attention is needed in the choice of diversity metrics necessary to effectively characterize biodiversity. We conclude by highlighting that this integrated framework provides a better understanding of dimensionality than considering only the correlation component.