Plants reward seed dispersers in proportion to their effort: the relationship between pulp mass and seed mass in vertebrate dispersed plants

In this paper I develop a null model for the expected relationship between seed mass and the mass of dispersal structure (reward) for vertebrate-dispersed plant species. The model is based on the simple assumption that the reward associated with a given seed mass is commensurate with work required to move it, and predicts that reward mass should scale relative to seed mass with an exponent of 4/3 (1.3). I tested this relationship between- and within-species of vertebrate-dispersed plants from four families from tropical rain forest in north Queensland, Australia. At a community-level there was a significant isometric relationship between log mean pulp mass and log mean seed mass across species. When family membership was considered, the estimate for the common slope between families was 1.32, surprisingly similar to the exponent predicted from commensurate reward. In addition, the 95% CI of the common slope did not include unity, providing no support for isometry. There was also no evidence that the relationships between mean log pulp mass and mean log seed mass were significantly different between families. This simple null model may be a common “rule” governing mean allocation to reward in all plant–animal dispersal mutualisms and its confirmation is the first evidence that animal dispersers have shaped the evolution of seed traits. However, I found no evidence that the scaling relationships within-species were consistently predicted by commensurate reward – a “taxon-level effect”. I suggest that the taxon-level effect arises because mean seed and mean reward mass within each species arises due to community-wide, disperser-mediated selection to produce equally attractive fruits, whereas within-species allometries may be determined by selection for fruit traits that enhance either dispersal probabilities, offspring survival or both, and these will be contingent on the environmental context into which seeds are released

The Multiple Sclerosis Data Alliance Catalogue: Enabling Web-Based Discovery of Metadata from Real-World Multiple Sclerosis Data Sources.

Background: One of the major objectives of the Multiple Sclerosis Data Alliance (MSDA) is to enable better discovery of multiple sclerosis (MS) real-world data (RWD). Methods: We implemented the MSDA Catalogue, which is available worldwide. The current version of the MSDA Catalogue collects descriptive information on governance, purpose, inclusion criteria, procedures for data quality control, and how and which data are collected, including the use of e-health technologies and data on collection of COVID-19 variables. The current cataloguing procedure is performed in several manual steps, securing an effective catalogue. Results: Herein we summarize the status of the MSDA Catalogue as of January 6, 2021. To date, 38 data sources across five continents are included in the MSDA Catalogue. These data sources differ in purpose, maturity, and variables collected, but this landscaping effort shows that there is substantial alignment on some domains. The MSDA Catalogue shows that personal data and basic disease data are the most collected categories of variables, whereas data on fatigue measurements and cognition scales are the least collected in MS registries/cohorts. Conclusions: The Web-based MSDA Catalogue provides strategic overview and allows authorized end users to browse metadata profiles of data cohorts and data sources. There are many existing and arising RWD sources in MS. Detailed cataloguing of MS RWD is a first and useful step toward reducing the time needed to discover MS RWD sets and promoting collaboration

COVID-19 in people with multiple sclerosis: A global data sharing initiative

BACKGROUND: We need high-quality data to assess the determinants for COVID-19 severity in people with MS (PwMS). Several studies have recently emerged but there is great benefit in aligning data collection efforts at a global scale. OBJECTIVES: Our mission is to scale-up COVID-19 data collection efforts and provide the MS community with data-driven insights as soon as possible. METHODS: Numerous stakeholders were brought together. Small dedicated interdisciplinary task forces were created to speed-up the formulation of the study design and work plan. First step was to agree upon a COVID-19 MS core data set. Second, we worked on providing a user-friendly and rapid pipeline to share COVID-19 data at a global scale. RESULTS: The COVID-19 MS core data set was agreed within 48 hours. To date, 23 data collection partners are involved and the first data imports have been performed successfully. Data processing and analysis is an on-going process. CONCLUSIONS: We reached a consensus on a core data set and established data sharing processes with multiple partners to address an urgent need for information to guide clinical practice. First results show that partners are motivated to share data to attain the ultimate joint goal: better understand the effect of COVID-19 in PwMS.status: publishe