An algorithm to reduce the occupational space in gender segregation studies

This paper presents an algorithm based on the bootstrap to select an admissible aggregation level, that is, the minimum number of occupational categories that yield a gender segregation value not significantly smaller than that obtained from the large number of occupational categories usually available in any data set. The approach is illustrated using labour force survey data for Spain for the comparison of gender segregation in 1977 and 1992, as well as 1994 and 2000. To measure gender segregation, an additively decomposable segregation index based on the entropy concept is used. Despite a substantial simplification in the size of the occupation space, the decrease in the segregation index is very small and not significant, regardless of the year. Consequently, intertemporal changes in gender segregation can be studied using a greatly reduced classification of occupations that permits an easier interpretation of results.Publicad

Finding flies in the mushroom soup : Host specificity of fungus-associated communities revisited with a novel molecular method

Fruiting bodies of fungi constitute an important resource for thousands of other taxa. The structure of these diverse assemblages has traditionally been studied with labour-intensive methods involving cultivation and morphology-based species identification, to which molecular information might offer convenient complements. To overcome challenges in DNA extraction and PCR associated with the complex chemical properties of fruiting bodies, we developed a pipeline applicable for extracting amplifiable total DNA from soft fungal samples of any size. Our protocol purifies DNA in two sequential steps: (a) initial salt-isopropanol extraction of all nucleic acids in the sample is followed by (b) an extra clean-up step using solid-phase reversible immobilization (SPRI) magnetic beads. The protocol proved highly efficient, with practically all of our samples-regardless of biomass or other properties-being successfully PCR-amplified using metabarcoding primers and subsequently sequenced. As a proof of concept, we apply our methods to address a topical ecological question: is host specificity a major characteristic of fungus-associated communities, that is, do different fungus species harbour different communities of associated organisms? Based on an analysis of 312 fungal fruiting bodies representing 10 species in five genera from three orders, we show that molecular methods are suitable for studying this rich natural microcosm. Comparing to previous knowledge based on rearing and morphology-based identifications, we find a species-rich assemblage characterized by a low degree of host specialization. Our method opens up new horizons for molecular analyses of fungus-associated interaction webs and communities.Peer reviewe

High-level classification of the Fungi and a tool for evolutionary ecological analyses

High-throughput sequencing studies generate vast amounts of taxonomic data. Evolutionary ecological hypotheses of the recovered taxa and Species Hypotheses are difficult to test due to problems with alignments and the lack of a phylogenetic backbone. We propose an updated phylum-and class-level fungal classification accounting for monophyly and divergence time so that the main taxonomic ranks are more informative. Based on phylogenies and divergence time estimates, we adopt phylum rank to Aphelidiomycota, Basidiobolomycota, Calcarisporiellomycota, Glomeromycota, Entomophthoromycota, Entorrhizomycota, Kickxellomycota, Monoblepharomycota, Mortierellomycota and Olpidiomycota. We accept nine subkingdoms to accommodate these 18 phyla. We consider the kingdom Nucleariae (phyla Nuclearida and Fonticulida) as a sister group to the Fungi. We also introduce a perl script and a newick-formatted classification backbone for assigning Species Hypotheses into a hierarchical taxonomic framework, using this or any other classification system. We provide an example of testing evolutionary ecological hypotheses based on a global soil fungal data set.Peer reviewe

Taxonomy based on science is necessary for global conservation

Peer reviewe

Biodiversity information services: a (not-so-) little knowledge that acts

Standards set up by Biodiversity Information Standards-Taxonomic Databases Working Group (TDWG), initially developed as a way to share taxonomical data, greatly facilitated the establishment of the Global Biodiversity Information Facility (GBIF) as the largest index to digitally-accessible primary biodiversity information records (PBR) held by many institutions around the world. The level of detail and coverage of the body of standards that later became the Darwin Core terms enabled increasingly precise retrieval of relevant records useful for increased digitally-accessible knowledge (DAK) which, in turn, may have helped to solve ecologically-relevant questions. After more than a decade of data accrual and release, an increasing number of papers and reports are citing GBIF either as a source of data or as a pointer to the original datasets. GBIF has curated a list of over 5,000 citations that were examined for contents, and to which tags were applied describing such contents as additional keywords. The list now provides a window on what users want to accomplish using such DAK. We performed a preliminary word frequency analysis of this literature, starting at titles, which refers to GBIF as a resource. Through a standardization and mapping of terms, we examined how the facility-enabled data seem to have been used by scientists and other practitioners through time: what concepts/issues are pervasive, which taxon groups are mostly addressed, and whether data concentrate around specific geographical or biogeographical regions. We hoped to cast light on which types of ecological problems the community believes are amenable to study through the judicious use of this data commons and found that, indeed, a few themes were distinctly more frequently mentioned than others. Among those, generally-perceived issues such as climate change and its effect on biodiversity at global and regional scales seemed prevalent. The taxonomic groups were also unevenly mentioned, with birds and plants being the most frequently named. However, the entire list of potential subjects that might have used GBIF-enabled data is now quite wide, showing that the availability of well-structured data has spawned a widening spectrum of possible use cases. Among them, some enjoy early and continuous presence (e.g. species, biodiversity, climate) while others have started to show up only later, once a critical mass of data seemed to have been attained (e.g. ecosystems, suitability, endemism). Biodiversity information in the form of standards-compliant DAK may thus already have become a commodity enabling insight into an increasingly more complex and diverse body of science. Paraphrasing Tennyson, more things were wrought by data than TDWG dreamt of

Want to Describe and Share Biodiversity Inventory and Monitoring Data? The Humboldt Extension for Ecological Inventories Can Help!

Access to high-quality ecological data is critical to assessing and modeling biodiversity and its changes through space and time. The Darwin Core standard has proven to be immensely helpful in sharing species occurrence data (see Wieczorek et al. 2012, Global Biodiversity Information Facility, GBIF) and promoting biodiversity research following the FAIR principles of findability, accessibility, interoperability and reusability (Wilkinson et al. 2016). However, it is limited in its ability to fully accommodate inventory data (i.e., linked records of multiple taxa at a specific place and time). Information about the inventory processes is often either unreported or described in an unstructured manner, limiting its potential re-use for larger-scale analyses. Two key aspects that are not captured in a structured manner yet are: i) information about the species that were not detected during an inventory, and ii) ancillary information about sampling effort and completeness.Non-detections (i.e., reported counts of zero) potentially enable more accurate and precise estimates of distribution, abundance, and changes in abundance. This becomes possible when variation in effort is used to estimate the likelihood that a non-detection represents a true absence of that taxon during the inventory. Currently, ecological inventory data, when shared at all, are typically discoverable through dataset catalogs (e.g., governmental data repositories) and supplementary materials to publications. With few exceptions, indexing of such data with the detail and structure needed has not been attempted at broad temporal and spatial scales, despite the potentially high value resulting from making inventory data more readily accessible.To address these limitations in documenting inventory data using the Darwin Core, Guralnick et al. (2018) proposed the Humboldt Core. Subsequent discussions within the biodiversity standards community made it clear that greater integration could be achieved by creating an extension of the Darwin Core, rather than developing a new standard in isolation. Extension design work began in 2021 and progress has been reported by Brenton (2021) and Sica et al. (2022). Over the last year the Humboldt Extension Task Group has sought advice from data providers and aggregators and updated its vocabulary terms. A challenging aspect has been creating terminology for the parent-child relationships (see Properties of Hierarchical Events) needed to describe surveys that may be as simple as a collection of checklists (one level of hierarchy) or as complex as species records from traps within plots along transects across habitats over multiple years (at least four levels of hierarchy). The Task Group has committed to completing a User Guide for the Humboldt Extension. Group members who contributed to the Darwin Core (Darwin Core Task Group 2009) and the Vocabulary Maintenance Specification (Vocabulary Maintenance Specification Task Group 2017) have provided valuable expertise on term refinement and process.Through ratification of the Humboldt Extension as a Darwin Core Event extension, we expect to provide the community with a usable solution, tied to well-established data publication mechanisms, for sharing and using inventory data. This effort promises to overcome a key bottleneck in the sharing of critically important ecological data, enhancing data discoverability, interoperability and re-use while lowering reporting burden and data and metadata heterogeneity. Global data aggregation initiatives, such as GBIF, will benefit from this development as they develop their data models and the range of standards and extensions they support. We anticipate that the Humboldt Extension will be attractive both to data publishers and data users, by facilitating the representation and indexing of data in richer, more meaningful ways. Despite the data-intensive nature of fundamental ecological research and applied monitoring for management and policy, ecological data have remained as one of the FAIR data frontiers. We anticipate that the Humboldt Extension will address most data exchange needs of all professional communities involved

MIReAD, a minimum information standard for reporting arthropod abundance data

Arthropods play a dominant role in natural and human-modified terrestrial ecosystem dynamics. Spatially-explicit arthropod population time-series data are crucial for statistical or mathematical models of these dynamics and assessment of their veterinary, medical, agricultural, and ecological impacts. Such data have been collected world-wide for over a century, but remain scattered and largely inaccessible. In particular, with the ever-present and growing threat of arthropod pests and vectors of infectious diseases, there are numerous historical and ongoing surveillance efforts, but the data are not reported in consistent formats and typically lack sufficient metadata to make reuse and re-analysis possible. Here, we present the first-ever minimum information standard for arthropod abundance, Minimum Information for Reusable Arthropod Abundance Data (MIReAD). Developed with broad stakeholder collaboration, it balances sufficiency for reuse with the practicality of preparing the data for submission. It is designed to optimize data (re)usability from the “FAIR,” (Findable, Accessible, Interoperable, and Reusable) principles of public data archiving (PDA). This standard will facilitate data unification across research initiatives and communities dedicated to surveillance for detection and control of vector-borne diseases and pests