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Two new species of the Chilean endemic genus Miersia (Gilliesieae, Allioideae, Amaryllidaceae) are described, M. stellata and M. raucoana, alongside morphological descriptions, a distribution map, illustrations, conservation status assessments, and an updated key to all species of Miersia. Additionally, phylogenetic analyses of DNA sequences were performed to inquire into the evolutionary affinities of both new species and the recently described, M. putaendensis, within the tribe Gilliesieae.

IntroductionMixed methods research intervention studies integrate quantitative evaluation approaches, such as randomized controlled trials and quasi-experimental designs, with qualitative research to evaluate the effectiveness, efficacy, or other results of an intervention or program. These types of studies, which have attracted growing attention in recent years, enhance the scope and rigor of the evaluation. While various frameworks that summarize the justifications for carrying out these types of studies and provide implementation guidance have been published in the last few years in the health sciences, we do not know whether such frameworks have been properly implemented in the social and educational sciences. This review examined the methodological features and reporting practices of mixed methods intervention studies aimed at increasing young people’s interest in STEM.MethodsA systematic search was carried out in APA PsycNET, ERIC, ProQuest, Scopus, and Web of Science, and a hand search in 20 journals. We included peer-reviewed English-language articles that reported intervention studies with a quantitative component measuring outcomes specific to increasing secondary school students’ interest in STEM fields, a qualitative component conducted before, during, or after the quantitative component, and evidence of integration of both components. Qualitative content analysis and ideal-type analysis were used to synthesize the findings.ResultsWe found 34 studies; the majority published in the last ten years. Several patterns of mixed methods application were described in these studies, illustrating the unique insights that can be gained by employing this methodology. The reporting quality of the included studies was generally adequate, especially regarding the justification for using a mixed methods intervention design and the integration of the quantitative and qualitative components. Nonetheless, a few reporting issues were observed, such as a lack of detail in the presentation of the mixed methods design, an inadequate description of the qualitative sampling and analysis techniques, and the absence of joint displays for representing integration.DiscussionAuthors must pay attention to these issues to ensure that the insights obtained by the use of mixed methods research are effectively communicated.

The underrepresentation of young people and particularly young women in many STEM fields has inspired various intervention programmes and research intended to boost their interest in these areas. The purpose of this scoping review is to examine the characteristics and effectiveness of interventions designed to encourage interest in STEM among secondary school students, particularly female students, over the past 20 years. A systematic search of the literature in five databases and additional search strategies resulted in identifying 215 studies evaluating interventions in different disciplinary fields. Data extraction and synthesis of these studies were carried out, focusing on the methodologies and theoretical foundations used. Twenty-five exemplars were selected to illustrate best practices in designing and evaluating interventions that address the various facets of young people's lack of interest in STEM. These interventions attempt to modify and/or manipulate multiple environmental and school factors to impact students' personal factors associated with STEM interest, such as achievement, self-perception of ability, and self-efficacy. Implications for the design of future interventions and potential outcomes are then discussed.

According to Escobar (2012), there are two kinds of floral appendages around the staminal tube or urn in Miersia: 1) the upper pair of appendages are of staminal origin and 2) the four lateral appendages, one pair on each side of the staminal tube, are of tepaliferous origin. Consequently, mentions to “tepaliferous appendages” in diagnoses, descriptions, identification key and figure captions of our recent article (García et al. 2022) should be changed to “floral appendages”, to denote the mixed nature of those structures in most species of Miersia.

Estimation of biodiversity patterns in poorly known areas is hampered by data availability and biased collecting efforts. To overcome the former, patterns can be estimated at higher taxonomic levels and larger spatial units. To deal with the latter, species distribution models (SDMs) can be employed. We explored the ability of higher-rank taxonomic units to surrogate patterns of species diversity at different aggregation levels and the use of SDMs to correct collection bias. We used Chile as a study case and employed three biodiversity measures (taxon richness, weighted endemism and turnover), four spatial aggregation levels or resolutions (100, 75, 50 and 25 km grid cells) and three taxonomic levels (species, genera and operational taxonomic units (OTUs)) to evaluate the spatial agreement of biodiversity measures. OTUs are monophyletic groups at the finest taxonomic resolution given the available phylogenetic information. We used a specimen database of 3684 species (84%) of the Chilean vascular flora and evaluated its redundancy. Agreement in spatial patterns was calculated using the fuzzy Kappa index. SDMs were generated for the three taxonomic levels to estimate taxon richness. For each spatial aggregation level, we calculated agreement between specimen-based and SDM-based richness and surrogacy among taxonomic levels with and without SDMs. Density of sampling for specimen-based data allowed for a resolution of 25 km before reaching a critical low redundancy value for all taxonomic levels. Genera and OTUs are good surrogates of species for all biodiversity measures, but their predictive power decreases with spatial scale. Agreement in richness patterns between taxonomic levels is greatest for SDMs at 100 and 75 km resolution, suggesting that biodiversity patterns are best estimated at 75 km resolution using SDMs for this data set. While these results cannot be extrapolated beyond the study area, this framework can be implemented in other data-deficient regions to describe biodiversity patterns and to choose the appropriate aggregation level for downstream biodiversity studies, such as spatial phylogenetics, where species-level data availability is a more generalized problem, since sequence data are normally available for only few species.