Example structure of data sent from a citizen science platformback to a collection management system, simple case

Illustrative example of data format following Darwin Core sent back from a citizen science platform to the relevant collection management system. Simple case : http://coldb.mnhn.fr/catalognumber/mnhn/p/p03558024 Illustration of the milestone28 document, worpackage 5.2 of the ICEDIG project

Example structure of data sent from a collection management system to a citizen science platform, simple case

Illustrative example of data format following Darwin Core to send from a collection management system to a citizen science platform. Simple case : http://coldb.mnhn.fr/catalognumber/mnhn/p/p03558024 Illustration of the milestone28 document, worpackage 5.2 of the ICEDIG project

The Myriapoda and Onychophora collection (MY) of the Muséum national d’Histoire naturelle (MNHN, Paris)

The Myriapoda and Onychophora collection dataset inventories the occurrence records of the collection of myriapods and onychophorans in the Muséum national d’Histoire naturelle, Paris. The dataset currently consists of 202 lots of onychophorans, representing all of those present, and almost ten thousand (9 795) lots of myriapods, representing 33 to 40% of the MNHN Myriapoda collection. This collection, which is of key historic importance, represents the results of two centuries of myriapod and onychophoran studies. The sources of the collection are worldwide, with a high representation for metropolitan France for the myriapods. None of the occurrences are yet georeferenced. Access to the dataset via the data portals of the MNHN and the GBIF has been made possible through the e-ReColNat project (ANR-11-INBS-0004). The Myriapoda and Onychophora collection of MNHN is actively expanding, hence both the collection and dataset are in continuous growth. The dataset can be accessed through the portals of GBIF at http://www.gbif.org/dataset/3287044c-8c48-4ad6-81d4-4908071bc8db and the MNHN at http://science.mnhn.fr/institution/mnhn/collection/my/item/search/form

Global Plant Extinction Risk Assessment Inform Novel Biodiversity Hotspots [PREPRINT].

Curbing biodiversity loss and its impact on ecosystem services, resilience and Nature’s Contributions to People is one of the main challenges of our generation (IPBES, 2019b, 2019a; Secretariat of the United Nations Convention on Biological Diversity, 2020). A global baseline assessment of the threat status of all of biodiversity is crucial to monitor the progress of conservation policies worldwide (Mace & al., 2000; Secretariat of the United Nations Convention on Biological Diversity, 2021) and target priority areas for conservation (Walker & al., 2021). However, the magnitude of the task seems insurmountable, as even listing the organisms already known to science is a challenge (Nic Lughadha & al., 2016; Borsch & al., 2020; Govaerts & al., 2021). A new approach is needed to overcome this stumbling block and scale-up the assessment of extinction risk. that analyses of natural history mega-datasets using artificial intelligence allows us to predict a baseline conservation status for all vascular plants and identify target areas for conservation corresponding to hotspots optimally capturing different aspects of biodiversity. We illustrate the strong potential of AI-based methods to reliably predict extinction risk on a global scale. Our approach not only retrieved recognized biodiversity hotspots but identified new areas that may guide future global conservation action (Myers & al., 2000; Brooks & al., 2006). To further work in this area and guide the targets of the post-2020 biodiversity framework (Díaz & al., 2020a; Secretariat of the United Nations Convention on Biological Diversity, 2020; Mair & al., 2021), it will be necessary to accelerate the acquisition of fundamental data and allow inclusion of social and economic factors (Possingham & Wilson, 2005)

The French Muséum national d'histoire naturelle vascular plant herbarium collection dataset

International audienceWe provide a quantitative description of the French national herbarium vascular plants collection dataset. Held at the Muséum national d'histoire naturelle, Paris, it currently comprises records for 5,400,000 specimens, representing 90% of the estimated total of specimens. Ninety nine percent of the specimen entries are linked to one or more images and 16% have field-collecting information available. This major botanical collection represents the results of over three centuries of exploration and study. The sources of the collection are global, with a strong representation for France, including overseas territories, and former French colonies. The compilation of this dataset was made possible through numerous national and international projects, the most important of which was linked to the renovation of the herbarium building. The vascular plant collection is actively expanding today, hence the continuous growth exhibited by the dataset, which can be fully accessed through the GBIF portal or the MNHN database portal (available at: https://science.mnhn.fr/institution/mnhn/collection/p/item/search/form). This dataset is a major source of data for systematics, global plants macroecological studies or conservation assessments

Penetrance estimation of Alzheimer disease in SORL1 loss-of-function variant carriers using a family-based strategy and stratification by APOE genotypes

International audienceAbstract Background Alzheimer disease (AD) is a common complex disorder with a high genetic component. Loss-of-function (LoF) SORL1 variants are one of the strongest AD genetic risk factors. Estimating their age-related penetrance is essential before putative use for genetic counseling or preventive trials. However, relative rarity and co-occurrence with the main AD risk factor, APOE -ε4, make such estimations difficult. Methods We proposed to estimate the age-related penetrance of SORL1 -LoF variants through a survival framework by estimating the conditional instantaneous risk combining (i) a baseline for non-carriers of SORL1- LoF variants, stratified by APOE-ε4 , derived from the Rotterdam study ( N = 12,255), and (ii) an age-dependent proportional hazard effect for SORL1- LoF variants estimated from 27 extended pedigrees (including 307 relatives ≥ 40 years old, 45 of them having genotyping information) recruited from the French reference center for young Alzheimer patients. We embedded this model into an expectation-maximization algorithm to accommodate for missing genotypes. To correct for ascertainment bias, proband phenotypes were omitted. Then, we assessed if our penetrance curves were concordant with age distributions of APOE -ε4-stratified SORL1- LoF variant carriers detected among sequencing data of 13,007 cases and 10,182 controls from European and American case-control study consortia. Results SORL1- LoF variants penetrance curves reached 100% (95% confidence interval [99–100%]) by age 70 among APOE -ε4ε4 carriers only, compared with 56% [40–72%] and 37% [26–51%] in ε4 heterozygous carriers and ε4 non-carriers, respectively. These estimates were fully consistent with observed age distributions of SORL1- LoF variant carriers in case-control study data. Conclusions We conclude that SORL1- LoF variants should be interpreted in light of APOE genotypes for future clinical applications