Abstract: Aim Here, we aim to: (a) investigate the local effect of environmental and anthropogenic factors on alien plant invasion in sub-Antarctic islands; and (b) explore whether and how functional traits affect alien species dependence on anthropogenic factors in these environments. Location Possession Island, Crozet archipelago (French sub-Antarctic islands). Methods Single-species distribution models were used to explore the effect of high-resolution topoclimatic and human-related variables on the occurrence of six alien plants colonizing French sub-Antarctic islands. Furthermore, plant responses to human-related variables and the effect of those variables in interaction with plant traits were analysed by means of a multi-species distribution model. This allowed identifying functional features mediating the influence of human activities on the occurrence probability of alien plant species. Results We observed two main invasion patterns: (a) species predicted to occur close to the introduction sites, whose occurrence probability appeared to be strongly affected by anthropogenic factors; and (b) species predicted to occur nearly everywhere on Possession Island, except in areas featuring particularly harsh climatic conditions. Differences in the influence of human-related variables on the occurrence of the alien species were mostly related to their life history, plant height and residence time, with perennial and low-statured species introduced earlier appearing less dependent on human-induced dispersal and disturbance. Conclusions We conclude that both topoclimatic and anthropogenic factors affect plant invasion on sub-Antarctic islands. Specifically, species predicted to occur close to their introduction sites appear much more dependent on human presence and activity, potentially due to the lack of key functional traits allowing them to spread successfully across Possession Island under the harsh sub-Antarctic climate. Yet, particularly severe abiotic conditions are a major constraint which equally limits the occurrence of all alien plants, irrespective of their dependence on anthropogenic factors.

Abstract: The accurate prediction of tides is vital for the operation of many industries, early warning of coastal flooding and scientific understanding of ocean processes. In this paper, we describe the creation method of a global dataset of tidal harmonics using NEMO (Nucleus for European Modelling of the Ocean) for the first time and an offline objective analysis scheme. Data are assimilated as part of a post-processing step, reducing the computational resources required. A reduced ensemble of tidal harmonics is generated, where each member is run for a shorter period of time than a central background state. This ensemble is used to estimate a single background covariance state, which is used for analysis. Output is validated using an ensemble of objective analyses. For each ensemble member, random selections of observations are omitted and validation is performed at these locations. Improvements in both Mean Absolute Error (MAE) and correlation coefficients (R2) are seen across all 6 of the largest diurnal and semi-diurnal constituents. MAEs in amplitude and phase are reduced by up to 78% and 89%, respectively, and correlations by as much as 0.14. In addition, the majority of locations (between 70 and 80%) see significant improvement.