Changes in rainfall amounts and patterns have been observed and are expected to continue in the near future with potentially significant ecological and societal consequences. Modelling vegetation responses to changes in rainfall is thus crucial to project water and carbon cycles in the future. In this study, we present the results of a new model-data intercomparison project, where we tested the ability of 10 terrestrial biosphere models to reproduce the observed sensitivity of ecosystem productivity to rainfall changes at 10 sites across the globe, in nine of which, rainfall exclusion and/or irrigation experiments had been performed. The key results are as follows: (a) Intermodel variation is generally large and model agreement varies with timescales. In severely water-limited sites, models only agree on the interannual variability of evapotranspiration and to a smaller extent on gross primary productivity. In more mesic sites, model agreement for both water and carbon fluxes is typically higher on fine (daily-monthly) timescales and reduces on longer (seasonal-annual) scales. (b) Models on average overestimate the relationship between ecosystem productivity and mean rainfall amounts across sites (in space) and have a low capacity in reproducing the temporal (interannual) sensitivity of vegetation productivity to annual rainfall at a given site, even though observation uncertainty is comparable to inter-model variability. (c) Most models reproduced the sign of the observed patterns in productivity changes in rainfall manipulation experiments but had a low capacity in reproducing the observed magnitude of productivity changes. Models better reproduced the observed productivity responses due to rainfall exclusion than addition. (d) All models attribute ecosystem productivity changes to the intensity of vegetation stress and peak leaf area, whereas the impact of the change in growing season length is negligible. The relative contribution of the peak leaf area and vegetation stress intensity was highly variable among models. K E Y W O R D S drought, irrigation, rainfall manipulation experiment, terrestrial biosphere models

Mild traumatic brain injury (mTBI) is the most common neurological insult and leads to long-lasting cognitive impairments. The immune system modulates brain functions and plays a key role in cognitive deficits, however, the relationship between TBI-induced changes in inflammation-related cytokine levels and cognitive consequences is unclear. This was investigated in the present study in two cohorts of individuals within 1 week of mTBI (n = 52, n = 43) and 54 matched healthy control subjects. Patients with mTBI were also followed up at 1 and 3 months post-injury. Measures included cognitive assessments and a 9-plex panel of serum cytokines including interleukin (IL)-1β, IL-4, IL-6, IL-8, IL-10, IL-12, chemokine ligand 2 (CCL2), interferon-γ (IFN-γ), and tumor necrosis factor-α (TNF-α). The contribution of cytokine levels to cognitive function was evaluated by multivariate linear regression analysis. The results showed that serum levels of IL-1β, IL-6, and CCL2 were acutely elevated in mTBI patients relative to controls; CCL2 level was remained high over 3 months whereas IL-1β and IL-6 levels were declined by 3 months post-injury. A high level of CCL2 was associated with greater severity of post-concussion symptoms (which survived in the multiple testing correction); elevated IL-1β was associated with worse working memory in acute phase (which failed in correction); and acute high CCL2 level predicted higher information processing speed at 3 months post-injury (which failed in correction). Thus, acute serum cytokine levels are useful for evaluating post-concussion symptoms and predicting cognitive outcome in participants with mTBI.

ObjectivePost-traumatic headache (PTH) is one of the most frequent and persistent physical symptoms following mild traumatic brain injury (mTBI) and develop in more than 50% of this population. This study aimed to investigate the periaqueductal grey (PAG)-seeded functional connectivity (FC) in patients with mTBI with acute post-traumatic headache (APTH) and further examine whether the FC can be used as a neural biomarker to identify patients developing chronic pain 3 months postinjury.Methods70 patients with mTBI underwent neuropsychological measurements and MRI scans within 7 days postinjury and 56 (80%) of patients were followed up at 3 months. 46 healthy controls completed the same protocol on recruitment to the study. PAG-seeded resting-state FC analysis was measured in 54 patients with mTBI with APTH, in comparison with 46 healthy volunteers.ResultsThe mTBI+APTH group presented significantly reduced PAG-seeded FC within the default mode network (DMN), compared with healthy volunteers group. The connectivity strength can also predict patients’ complaints on the impact of headache on their lives. Crucially, the initial FC strength between the PAG-right precuneus as well as the PAG-right inferior parietal lobule became the important predictor to identify patients with mTBI developing persistent PTH 3 months postinjury.ConclusionsPatients with mTBI+APTH exhibited significant PAG-related FC differences mainly within the DMN. These regions extended beyond traditional pain processing areas and may reflect the diminished top-down attention regulation of pain perception through antinociceptive descending modulation network. The disrupted PAG-DMN FC may be used as an early imaging biomarker to identify patients at risk of developing persistent PTH.

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