Self-facilitation and negative species interactions could drive microscale vegetation mosaic in a floating fen

Aim: The formation of a local vegetation mosaic may be attributed to local variation in abiotic environmental conditions. Recent research, however, indicates that self-facilitating organisms and negative species interactions may be a driving factor. In this study, we explore whether heterogeneous geohydrological conditions or vegetation feedbacks and interactions could be responsible for a vegetation mosaic of rich and poor fen species. Location: Lake Aturtaun, Roundstone Bog, Ireland. Methods: In a floating fen, transects were set out to analyze the relation between vegetation type and rock–peat distance and porewater electrical conductivity. Furthermore, three distinct vegetation types were studied: rich fen, poor fen and patches of poor fen within rich fen vegetation. Biogeochemical measurements were conducted in a vertical profile to distinguish abiotic conditions of distinct vegetation types. Results: Geohydrological conditions may drive the distribution of poor and rich fen species at a larger scale in the floating fen, due to the supply of minerotrophic groundwater. Interestingly, both rich and poor fen vegetation occurred in a mosaic, when electrical conductivity values at 50 cm depth were between 300 µS/cm and 450 µS/cm. Although environmental conditions were homogeneous at 50 cm, they differed markedly between rich and poor fen vegetation at 10 cm depth. Specifically, our measurements indicate that poor fen vegetation lowered porewater alkalinity, bicarbonate concentrations and pH. No effects of rich fen vegetation at 10 cm depth on biogeochemistry was measured. However, rich fen litter had a higher mineralization rate than poor fen litter, which increases the influence of minerotrophic water in rich fen habitat. Conclusions: These results strengthen our hypothesis that species can drive formation of vegetation mosaics under environmentally homogeneous conditions in a floating fen. Positive intraspecific self-facilitating mechanisms and negative species interactions could be responsible for a stable coexistence of species, even leading to local ecosystem engineering by the species, explaining the local vegetation mosaic at the microscale level in a floating fen

Wetscapes : Restoring and maintaining peatland landscapes for sustainable futures

Peatlands are among the world's most carbon-dense ecosystems and hotspots of carbon storage. Although peatland drainage causes strong carbon emissions, land subsidence, fires and biodiversity loss, drainage-based agriculture and forestry on peatland is still expanding on a global scale. To maintain and restore their vital carbon sequestration and storage function and to reach the goals of the Paris Agreement, rewetting and restoration of all drained and degraded peatlands is urgently required. However, socio-economic conditions and hydrological constraints hitherto prevent rewetting and restoration on large scale, which calls for rethinking landscape use. We here argue that creating integrated wetscapes (wet peatland landscapes), including nature preserve cores, buffer zones and paludiculture areas (for wet productive land use), will enable sustainable and complementary land-use functions on the landscape level. As such, transforming landscapes into wetscapes presents an inevitable, novel, ecologically and socio-economically sound alternative for drainage-based peatland use

Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease: a meta-analysis of genome-wide association studies

Background Genome-wide association studies (GWAS) in Parkinson's disease have increased the scope of biological knowledge about the disease over the past decade. We aimed to use the largest aggregate of GWAS data to identify novel risk loci and gain further insight into the causes of Parkinson's disease. Methods We did a meta-analysis of 17 datasets from Parkinson's disease GWAS available from European ancestry samples to nominate novel loci for disease risk. These datasets incorporated all available data. We then used these data to estimate heritable risk and develop predictive models of this heritability. We also used large gene expression and methylation resources to examine possible functional consequences as well as tissue, cell type, and biological pathway enrichments for the identified risk factors. Additionally, we examined shared genetic risk between Parkinson's disease and other phenotypes of interest via genetic correlations followed by Mendelian randomisation. Findings Between Oct 1, 2017, and Aug 9, 2018, we analysed 7·8 million single nucleotide polymorphisms in 37 688 cases, 18 618 UK Biobank proxy-cases (ie, individuals who do not have Parkinson's disease but have a first degree relative that does), and 1·4 million controls. We identified 90 independent genome-wide significant risk signals across 78 genomic regions, including 38 novel independent risk signals in 37 loci. These 90 variants explained 16–36% of the heritable risk of Parkinson's disease depending on prevalence. Integrating methylation and expression data within a Mendelian randomisation framework identified putatively associated genes at 70 risk signals underlying GWAS loci for follow-up functional studies. Tissue-specific expression enrichment analyses suggested Parkinson's disease loci were heavily brain-enriched, with specific neuronal cell types being implicated from single cell data. We found significant genetic correlations with brain volumes (false discovery rate-adjusted p=0·0035 for intracranial volume, p=0·024 for putamen volume), smoking status (p=0·024), and educational attainment (p=0·038). Mendelian randomisation between cognitive performance and Parkinson's disease risk showed a robust association (p=8·00 × 10−7). Interpretation These data provide the most comprehensive survey of genetic risk within Parkinson's disease to date, to the best of our knowledge, by revealing many additional Parkinson's disease risk loci, providing a biological context for these risk factors, and showing that a considerable genetic component of this disease remains unidentified. These associations derived from European ancestry datasets will need to be followed-up with more diverse data. Funding The National Institute on Aging at the National Institutes of Health (USA), The Michael J Fox Foundation, and The Parkinson's Foundation (see appendix for full list of funding sources)

Correction: Wetscapes: Restoring and maintaining peatland landscapes for sustainable futures

Correction to: Ambio https://doi.org/10.1007/s13280-023-01875-