Biology subjects

Rocca, M. A.

Publications and source records attributed to Rocca, M. A..

3 recordsLinked to original sources

bioRxiv2018

Abundance drives generalisation in hummingbird-plant pollination networks

Abundant pollinators are often more generalised than rare pollinators. This could be because abundance drives generalisation: neutral effects suggest that more abundant species will be more generalised simply because they have more chance encounters with potential interaction partners. On the other hand, generalisation could drive abundance, as generalised species could have a competitive advantage over specialists, being able to exploit a wider range of resources and gain a more balanced nutrient intake. Determining the direction of the abundance-generalisation relationship is therefore a chicken-and-egg dilemma. Here we determine the direction of the relationship between abundance and generalisation in plant-hummingbird pollination networks sampled from a variety of locations across the Americas. For the first time we resolve the direction of the abundance-generalisation relationship using independent data on animal abundance. We find evidence that hummingbird pollinators are generalised because they are abundant, and little evidence that hummingbirds are abundant because they are generalised. Additionally, a null model analysis suggests this pattern is due to neutral processes: most patterns of species-level abundance and generalisation were well explained by a null model that assumed interaction neutrality. These results suggest that neutral processes play a key role in driving broad patterns of generalisation in animal pollinators across large spatial scales.\n\nDeclarationsFunding - BIS is supported by the Natural Environment Research Council as part of the Cambridge Earth System Science NERC DTP [NE/L002507/1]. JVB was funded by CERL - Engineer Research and Development Center. PKM was funded by the Sao Paulo Research Foundation (FAPESP grant #2015/21457-4). PAC was funded by the David Lack studentship from the British Ornithologists Union and Wolfson College, University of Oxford. CL was funded by the ESDEPED-UAT grant. MAM acknowledges the Consejo Nacional para Investigaciones Cientificas y Tecnologicas (Costa Rica), German Academic Exchange Service and the research funding program LOEWE-Landes-Offensive zur Entwicklung Wissenschaftlicho konomischer Exzellenz of Hesses Ministry of Higher Education, Research, and the Arts (Germany). ROP was funded by CONACyT (project 258364). MAR was supported by the State of Sao Paulo Research Foundation (FAPESP) within the BIOTA/FAPESP, The Biodiversity Institute Program (www.biota.org.br) and the Parcelas Permanentes project, as well as by Coordenacao de Pessoal de Nivel Superior (CAPES), Fundo de Apoio ao Ensino e a Pesquisa (FAEP)/Funcamp/Unicamp and The Nature Conservancy (TNC) of Brazil. LCR was supported by CNPq and Capes. MS was funded by CNPq (grant #302781/2016-1). AMMG is supported through a Marie Skodowska-Curie Individual Fellowship (H2020-MSCA-IF-2016-704409). LVD was supported by the Natural Environment Research Council (grants NE/K015419/1 and NE/N014472/1). AMMG, JS, CR and BD thank the Danish National Research Foundation for its support of the Center for Macroecology, Evolution and Climate (grant no. DNRF96). WJS is funded by Arcadia.

ecology↗

bioRxiv2017

Progression of regional grey matter atrophy in multiple sclerosis

Grey matter atrophy is present from the earliest clinical stages of multiple sclerosis (MS), but the temporal ordering is poorly understood. We aimed to determine the sequence in which grey matter regions become atrophic in MS, and its association with disability accumulation.\n\nIn this longitudinal study, we included 1,417 subjects: 253 with clinically-isolated syndrome (CIS), 708 relapsing-remitting MS (RRMS), 128 secondary-progressive MS (SPMS), 125 primary-progressive MS (PPMS), and 203 healthy controls from 7 European centres. Subjects underwent repeated MRI scanning (total number of scans 3,604); the mean follow-up for patients was 2.41yrs (SD{+/-}1.97). Disability was scored using the Expanded Disability Status Scale (EDSS). We calculated the volume of brain grey matter regions and brainstem using an unbiased within-subject template. We used an established data-driven event-based model (EBM) to determine the sequence of occurrence of atrophy and its uncertainty. We assigned each subject to a specific EBM stage, based on the number of their atrophic regions. We used nested linear mixed-effects regression models to explore the associations between the rate of increase in the EBM stages over time, disease duration and annual rate of EDSS gain.\n\nThe first regions to become atrophic in CIS and relapse-onset MS patients (RRMS and SPMS) were the posterior cingulate cortex and precuneus, followed by the middle cingulate cortex, brainstem and thalamus. The sequence of atrophy in PPMS showed a similar involvement of the thalamus, cuneus, precuneus, and pallidum, followed by the brainstem and posterior cingulate cortex. The cerebellum, caudate and putamen showed early atrophy in relapse-onset MS and late atrophy in PPMS. Patients with SPMS showed the highest EBM stages (highest number of atrophic regions, all p<0.001) at study entry. Rates of increase in EBM stages were significantly different from healthy controls in all MS phenotypes, except for CIS. The increase in the number of atrophic regions (EBM stage) was associated with disease duration in all patients. EBM stage was associated with disability accumulation in RRMS independent of disease duration (p<0.0001).\n\nThis data-driven staging of atrophy progression in a large MS sample demonstrates that grey matter atrophy spreads to involve more regions over time. The sequence in which regions become atrophic is reasonably consistent across MS phenotypes. The spread of atrophy was associated with disease duration, and disability accumulation in RRMS.\n\nAbbreviations

neuroscience↗

bioRxiv2017

Deep grey matter volume loss drives disability worsening in multiple sclerosis

ObjectiveGrey matter (GM) atrophy occurs in all multiple sclerosis (MS) phenotypes. We investigated whether there is a spatiotemporal pattern of GM atrophy that is associated with faster disability accumulation in MS.\n\nMethodsWe analysed 3,604 brain high-resolution T1-weighted MRI scans from 1,417 participants: 1,214 MS patients (253 clinically-isolated syndrome[CIS], 708 relapsingremitting[RRMS], 128 secondary-progressive[SPMS], 125 primary-progressive[PPMS]), over an average follow-up of 2.41 years (standard deviation[SD]=1.97), and 203 healthy controls (HCs) [average follow-up=1.83 year, SD=1.77], attending 7 European centres. Disability was assessed with the Expanded-Disability Status Scale (EDSS). We obtained volumes of the deep GM (DGM), temporal, frontal, parietal, occipital and cerebellar GM, brainstem and cerebral white matter. Hierarchical mixed-models assessed annual percentage rate of regional tissue loss and identified regional volumes associated with time-to-EDSS progression.\n\nResultsSPMS showed the lowest baseline volumes of cortical GM and DGM. Of all baseline regional volumes, only that of the DGM predicted time-to-EDSS progression (hazard ratio=0.73, 95% CIs 0.65, 0.82; p<0.001): for every standard deviation decrease in baseline DGM volume, the risk of presenting a shorter time to EDSS worsening during follow-up increased by 27%. Of all longitudinal measures, DGM showed the fastest annual rate of atrophy, which was faster in SPMS (-1.45%), PPMS (-1.66%), and RRMS (-1.34%) than CIS (-0.88%) and HCs (-0.94%)[p<0.01]. The rate of temporal GM atrophy in SPMS (-1.21%) was significantly faster than RRMS (-0.76%), CIS (-0.75%), and HCs (-0.51%). Similarly, the rate of parietal GM atrophy in SPMS (-1.24-%) was faster than CIS (-0.63%) and HCs (-0.23%) (all p values <0.05). Only the atrophy rate in DGM in patients was significantly associated with disability accumulation (beta=0.04, p<0.001).\n\nInterpretationThis large multi-centre and longitudinal study shows that DGM volume loss drives disability accumulation in MS, and that temporal cortical GM shows accelerated atrophy in SPMS than RRMS. The difference in regional GM atrophy development between phenotypes needs to be taken into account when evaluating treatment effect of therapeutic interventions.

neuroscience↗