1,338 research outputs found

    “Pifá, Bananas, Oranges Are Our Forests”: Agroforestry and Development among Smallholder Farmers in Panama

    Get PDF
    Deforestation and forest fragmentation continue unabated in many parts of the world. Scholars point to the expansion of the agricultural frontier as a driver of forest and biodiversity loss. Government agencies and non-governmental organizations (NGOs) often promote agroforestry as a sustainable development strategy for combating deforestation while improving the livelihoods of smallholder farmers. Yet agroforestry projects designed by outsiders who have technical expertise but relatively little local or traditional knowledge can bring negative outcomes for farmers, local communities, and farmer associations. Prescriptive ideas from governments and NGOs may clash with or even contradict local understandings and practices of how forests, fields, and resources should be managed. Though farmers may participate in state and outsider projects, their decisions to embrace, ignore, or negotiate on their own terms how resources are managed ultimately determine the contents and contours of agricultural and forest landscapes. The Panamanian government’s Ministry of Environment, national institutions, and NGOs are promoting agroforestry projects among smallholder farmer association members. I compare the perspectives of farmer association members, non-members, and NGO and government staff to examine how farmers practice agroforestry, the reported benefits of agroforestry, the value of being part of a farmer association, and how agroforestry is supporting (or not) conservation in the Santa Maria River watershed and in the outskirts of Santa Fe National Park in Panama. Results of the research show how micro-level natural resource management of smallholder farmers and livelihood strategies is linked with macro-level projects and discourse about agroforestry. Methods include semi-structured interviews, participatory mapping, and participant observation among smallholder farmers and NGO and government staff as well as the placement of camera traps on farms and in SFNP. The twenty-month ethnographic study reveals how farmers respond to the messages of environmental NGOs, government, and other outside actors. The significance of the project is in increasing knowledge about the complexities of managing natural resources for conservation while improving livelihoods

    The Pediatric Asthma Risk Score: A New Gold Standard for Asthma Prediction

    Get PDF
    Rationale: Early prediction of asthma is critical to identify potential primary prevention strategies. The Pediatric Asthma Risk Score (PARS) is a continuous score to predict early-life asthma but was developed and validated in relatively homogenous populations. We compared PARS directly to the Asthma Predictive Index (API) and validated in 10 cohorts with varying race, ethnicity, sex, cohort type, missing data and birth decades, and perform a meta-analysis across all 10 cohorts. Methods: We utilized data from 5674 children participating in the Children’s Respiratory and Environmental Workgroup. We applied both PARS and the API in each cohort, as well as harmonized across all cohorts, and directly compared the ability of each tool to predict asthma development at ages 5-10. Results: The PARS area under the curve (AUC) was significantly higher than the AUC of the API in 9 cohorts (p-value range 0.01 - \u3c0.001). The PARS AUC did not differ by cohort type (high risk or general population), decade of enrollment, race, sex, ethnicity, missing PARS factors or polysensitization definition (skin prick test vs. specific IgE). The weights of the 6 PARS factors in the meta-analysis were very similar to the original weights, validating the original PARS scoring. Conclusions: This multi-cohort study makes the PARS the most validated model of asthma prediction in children to date, not only with respect to the number of cohorts used but also with regards to capturing the diversity of asthma in the United States. Future studies may consider PARS the new gold standard in pediatric asthma risk prediction

    DNM1 encephalopathy: A new disease of vesicle fission.

    Get PDF
    ObjectiveTo evaluate the phenotypic spectrum caused by mutations in dynamin 1 (DNM1), encoding the presynaptic protein DNM1, and to investigate possible genotype-phenotype correlations and predicted functional consequences based on structural modeling.MethodsWe reviewed phenotypic data of 21 patients (7 previously published) with DNM1 mutations. We compared mutation data to known functional data and undertook biomolecular modeling to assess the effect of the mutations on protein function.ResultsWe identified 19 patients with de novo mutations in DNM1 and a sibling pair who had an inherited mutation from a mosaic parent. Seven patients (33.3%) carried the recurrent p.Arg237Trp mutation. A common phenotype emerged that included severe to profound intellectual disability and muscular hypotonia in all patients and an epilepsy characterized by infantile spasms in 16 of 21 patients, frequently evolving into Lennox-Gastaut syndrome. Two patients had profound global developmental delay without seizures. In addition, we describe a single patient with normal development before the onset of a catastrophic epilepsy, consistent with febrile infection-related epilepsy syndrome at 4 years. All mutations cluster within the GTPase or middle domains, and structural modeling and existing functional data suggest a dominant-negative effect on DMN1 function.ConclusionsThe phenotypic spectrum of DNM1-related encephalopathy is relatively homogeneous, in contrast to many other genetic epilepsies. Up to one-third of patients carry the recurrent p.Arg237Trp variant, which is now one of the most common recurrent variants in epileptic encephalopathies identified to date. Given the predicted dominant-negative mechanism of this mutation, this variant presents a prime target for therapeutic intervention

    Examining the reproducibility of meta-analyses in psychology:A preliminary report

    Get PDF
    Meta-analyses are an important tool to evaluate the literature. It is essential that meta-analyses can easily be reproduced to allow researchers to evaluate the impact of subjective choices on meta-analytic effect sizes, but also to update meta-analyses as new data comes in, or as novel statistical techniques (for example to correct for publication bias) are developed. Research in medicine has revealed meta-analyses often cannot be reproduced. In this project, we examined the reproducibility of meta-analyses in psychology by reproducing twenty published meta-analyses. Reproducing published meta-analyses was surprisingly difficult. 96% of meta-analyses published in 2013-2014 did not adhere to reporting guidelines. A third of these meta-analyses did not contain a table specifying all individual effect sizes. Five of the 20 randomly selected meta-analyses we attempted to reproduce could not be reproduced at all due to lack of access to raw data, no details about the effect sizes extracted from each study, or a lack of information about how effect sizes were coded. In the remaining meta-analyses, differences between the reported and reproduced effect size or sample size were common. We discuss a range of possible improvements, such as more clearly indicating which data were used to calculate an effect size, specifying all individual effect sizes, adding detailed information about equations that are used, and how multiple effect size estimates from the same study are combined, but also sharing raw data retrieved from original authors, or unpublished research reports. This project clearly illustrates there is a lot of room for improvement when it comes to the transparency and reproducibility of published meta-analyses
    • 

    corecore