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The path signature is a means of feature generation that can encode nonlinear interactions in data in addition to the usual linear terms. It provides interpretable features and its output is a fixed length vector irrespective of the number of input points or their sample times. In this paper we use the path signature to provide features for identifying people whose diagnosis subsequently converts to Alzheimer's disease. In two separate classification tasks we distinguish converters from 1) healthy individuals, and 2) individuals with mild cognitive impairment. The data used are time-ordered measurements of the whole brain, ventricles and hippocampus from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We find two nonlinear interactions which are predictive in both cases. The first interaction is change of hippocampal volume with time, and the second is a change of hippocampal volume relative to the volume of the whole brain. While hippocampal and brain volume changes are well known in Alzheimer's disease, we demonstrate the power of the path signature in their identification and analysis without manual feature selection. Sequential data is becoming increasingly available as monitoring technology is applied, and the path signature method is shown to be a useful tool in the processing of this data.

Tree-ring records can provide valuable information to advance our understanding of contemporary terrestrial carbon cycling and to reconstruct key metrics in the decades preceding monitoring data. The growing use of tree rings in carbon-cycle research is being facilitated by increasing recognition of reciprocal benefits among research communities. Yet, basic questions persist regarding what tree rings represent at the ecosystem level, how to optimally integrate them with other data streams, and what related challenges need to be overcome. It is also apparent that considerable unexplored potential exists for tree rings to refine assessments of terrestrial carbon cycling across a range of temporal and spatial domains. Here, we summarize recent advances and highlight promising paths of investigation with respect to (1) growth phenology, (2) forest productivity trends and variability, (3) CO₂ fertilization and water-use efficiency, (4) forest disturbances, and (5) comparisons between observational and computational forest productivity estimates. We encourage the integration of tree-ring data: with eddy-covariance measurements to investigate carbon allocation patterns and water-use efficiency; with remotely sensed observations to distinguish the timing of cambial growth and leaf phenology; and with forest inventories to develop continuous, annually-resolved and long-term carbon budgets. In addition, we note the potential of tree-ring records and derivatives thereof to help evaluate the performance of earth system models regarding the simulated magnitude and dynamics of forest carbon uptake, and inform these models about growth responses to (non-)climatic drivers. Such efforts are expected to improve our understanding of forest carbon cycling and place current developments into a long-term perspective.

Rising atmospheric CO₂ and warming spring temperatures increase vegetation growth and the terrestrial carbon sink. However, drought, heat stress, phenology, and resource limitations may stabilize or limit theses projected increases. We investigate the balance between these amplifying and stabilizing ecological factors by asking whether enhanced early-season growth leads to continued late-season growth. Using the Moderate Resolution Imaging Spectroradiometer (MODIS) leaf area index (LAI) dataset, we identify three seasonal growth patterns based on early- and peak-season positive LAI anomalies: (1) amplification, where late-season LAI anomalies exceed earlier ones; (2) weak stabilization, where late-season anomalies remain similar or slightly lower; and (3) strong stabilization, where late-season anomalies become negative. Weak and strong stabilization events dominate across 67% and 26% of Northern Hemisphere ecosystems above 30°N, respectively. The absence of any trend in amplifying or stabilizing events suggests stabilizing factors seasonally offset CO₂ and temperature-induced spring greening. Terrestrial biosphere models underestimate strong stabilization and overestimate amplification events. This inconsistency arises from the models’ underestimation late-season LAI sensitivity to precipitation in water-limited regions; overlook negative legacy effects of early enhanced LAI on late-season soil moisture via evapotranspiration losses in energy-limited regions. Our findings suggest water/heat stress and resource limitations limit greening and the land carbon sink. Rising CO₂ and warming enhance vegetation greening, but drought, heat stress, and resource limits constrain this trend. Here, the authors show that within a year, increased early- and peak- season greenness often leads to late-season declines, highlighting water/heat stress limits on greening and the carbon sink.

Earth's future carbon balance and regional carbon exchange dynamics are inextricably linked to plant photosynthesis. Spectral vegetation indices are widely used as proxies for vegetation greenness and to estimate state variables such as vegetation cover and leaf area index. However, the capacity of green leaves to take up carbon can change throughout the season. We quantify photosynthetic capacity as the maximum rate of RuBP carboxylation (Vcmax) and regeneration (Jmax). Vcmax and Jmax vary within-season due to interactions between ontogenetic processes and meteorological variables. Remote sensing-based estimation of Vcmax and Jmax using leaf reflectance spectra is promising, but temporal variation in relationships between these key determinants of photosynthetic capacity, leaf reflectance spectra, and the models that link these variables has not been evaluated. To address this issue, we studied hybrid poplar (Populus spp.) during a 7-week mid-summer period to quantify seasonally-dynamic relationships between Vcmax, Jmax, and leaf spectra. We compared in situ estimates of Vcmax and Jmax from gas exchange measurements to estimates of Vcmax and Jmax derived from partial least squares regression (PLSR) and fresh-leaf reflectance spectroscopy. PLSR models were robust despite dynamic temporal variation in Vcmax and Jmax throughout the study period. Within-population variation in plant stress modestly reduced PLSR model predictive capacity. Hyperspectral vegetation indices were well-correlated to Vcmax and Jmax, including the widely-used Normalized Difference Vegetation Index. Our results show that hyperspectral estimation of plant physiological traits using PLSR may be robust to temporal variation. Additionally, hyperspectral vegetation indices may be sufficient to detect temporal changes in photosynthetic capacity in contexts similar to those studied here. Overall, our results highlight the potential for hyperspectral remote sensing to estimate determinants of photosynthetic capacity during periods with dynamic temporal variations related to seasonality and plant stress, thereby improving estimates of plant productivity and characterization of the associated carbon budget.

Hybrid-poplar tree plantations provide a source for biofuel and biomass, but they also increase forest isoprene emissions. The consequences of increased isoprene emissions include higher rates of tropospheric ozone production, increases in the lifetime of methane, and increases in atmospheric aerosol production, all of which affect the global energy budget and/or lead to the degradation of air quality. Using RNA interference (RNAi) to suppress isoprene emission, we show that this trait, which is thought to be required for the tolerance of abiotic stress, is not required for high rates of photosynthesis and woody biomass production in the agroforest plantation environment, even in areas with high levels of climatic stress. Biomass production over 4 y in plantations in Arizona and Oregon was similar among genetic lines that emitted or did not emit significant amounts of isoprene. Lines that had substantially reduced isoprene emission rates also showed decreases in flavonol pigments, which reduce oxidative damage during extremes of abiotic stress, a pattern that would be expected to amplify metabolic dysfunction in the absence of isoprene production in stress-prone climate regimes. However, compensatory increases in the expression of other proteomic components, especially those associated with the production of protective compounds, such as carotenoids and terpenoids, and the fact that most biomass is produced prior to the hottest and driest part of the growing season explain the observed pattern of high biomass production with low isoprene emission. Our results show that it is possible to reduce the deleterious influences of isoprene on the atmosphere, while sustaining woody biomass production in temperate agroforest plantations.

We review how intertidal biodiversity is responding to globally driven climate change, focusing on long-term data from rocky shores in the British Isles. Physical evidence of warming around the British Isles is presented and, whilst there has been considerable fluctuation, sea surface temperatures are at the highest levels recorded, surpassing previous warm periods (i.e. late 1950s). Examples are given of species that have been advancing or retreating polewards over the last 50 to 100 yr. On rocky shores, the extent of poleward movement is idiosyncratic and dependent upon life history characteristics, dispersal capabilities and habitat requirements. More southern, warm water species have been recorded advancing than northern, cold water species retreating. Models have been developed to predict likely assemblage composition based on future environmental scenarios. We present qualitative and quantitative forecasts to explore the functional consequences of changes in the identity, abundance and species richness of gastropod grazers and foundation species such as barnacles and canopy-forming algae. We forecast that the balance of primary producers and secondary consumers is likely to change along wave exposure gradients matching changes occurring with latitude, thereby shifting the balance between export and import of primary production. Increases in grazer and sessile invertebrate diversity are likely to be accompanied by decreasing primary production by large canopy-forming fucoids. The reasons for such changes are discussed in the context of emerging theory on the relationship between biodiversity and ecosystem functioning.

Summary Atmospheric carbon dioxide concentration ([CO2]) is increasing, which increases leaf‐scale photosynthesis and intrinsic water‐use efficiency. These direct responses have the potential to increase plant growth, vegetation biomass, and soil organic matter; transferring carbon from the atmosphere into terrestrial ecosystems (a carbon sink). A substantial global terrestrial carbon sink would slow the rate of [CO2] increase and thus climate change. However, ecosystem CO2 responses are complex or confounded by concurrent changes in multiple agents of global change and evidence for a [CO2]‐driven terrestrial carbon sink can appear contradictory. Here we synthesize theory and broad, multidisciplinary evidence for the effects of increasing [CO2] (iCO2) on the global terrestrial carbon sink. Evidence suggests a substantial increase in global photosynthesis since pre‐industrial times. Established theory, supported by experiments, indicates that iCO2 is likely responsible for about half of the increase. Global carbon budgeting, atmospheric data, and forest inventories indicate a historical carbon sink, and these apparent iCO2 responses are high in comparison to experiments and predictions from theory. Plant mortality and soil carbon iCO2 responses are highly uncertain. In conclusion, a range of evidence supports a positive terrestrial carbon sink in response to iCO2, albeit with uncertain magnitude and strong suggestion of a role for additional agents of global change. See also the Commentary on this article by Way et al., 229: 2383–2385.

Plant activity in semi-arid ecosystems is largely controlled by pulses of precipitation, making them particularly vulnerable to increased aridity that is expected with climate change. Simple bucket-model hydrology schemes in land surface models (LSMs) have had limited ability in accurately capturing semi-arid water stores and fluxes. Recent, more complex, LSM hydrology models have not been widely evaluated against semi-arid ecosystem in situ data. We hypothesize that the failure of older LSM versions to represent evapotranspiration, ET, in arid lands is because simple bucket models do not capture realistic fluctuations in upper-layer soil moisture. We therefore predict that including a discretized soil hydrology scheme based on a mechanistic description of moisture diffusion will result in an improvement in model ET when compared to data because the temporal variability of upper-layer soil moisture content better corresponds to that of precipitation inputs. To test this prediction, we compared ORCHIDEE LSM simulations from (1) a simple conceptual 2-layer bucket scheme with fixed hydraulic parameters and (2) an 11-layer discretized mechanistic scheme of moisture diffusion in unsaturated soil based on Richards equations, against daily and monthly soil moisture and ET observations, together with data-derived estimates of transpiration / evapotranspiration, T∕ET, ratios, from six semi-arid grass, shrub, and forest sites in the south-western USA. The 11-layer scheme also has modified calculations of surface runoff, water limitation, and resistance to bare soil evaporation, E, to be compatible with the more complex hydrology configuration. To diagnose remaining discrepancies in the 11-layer model, we tested two further configurations: (i) the addition of a term that captures bare soil evaporation resistance to dry soil; and (ii) reduced bare soil fractional vegetation cover. We found that the more mechanistic 11-layer model results in a better representation of the daily and monthly ET observations. We show that, as predicted, this is because of improved simulation of soil moisture in the upper layers of soil (top ∼ 10 cm). Some discrepancies between observed and modelled soil moisture and ET may allow us to prioritize future model development and the collection of additional data. Biases in winter and spring soil moisture at the forest sites could be explained by inaccurate soil moisture data during periods of soil freezing and/or underestimated snow forcing data. Although ET is generally well captured by the 11-layer model, modelled T∕ET ratios were generally lower than estimated values across all sites, particularly during the monsoon season. Adding a soil resistance term generally decreased simulated bare soil evaporation, E, and increased soil moisture content, thus increasing transpiration, T, and reducing the negative bias between modelled and estimated monsoon T∕ET ratios. This negative bias could also be accounted for at the low-elevation sites by decreasing the model bare soil fraction, thus increasing the amount of transpiring leaf area. However, adding the bare soil resistance term and decreasing the bare soil fraction both degraded the model fit to ET observations. Furthermore, remaining discrepancies in the timing of the transition from minimum T∕ET ratios during the hot, dry May–June period to high values at the start of the monsoon in July–August may also point towards incorrect modelling of leaf phenology and vegetation growth in response to monsoon rains. We conclude that a discretized soil hydrology scheme and associated developments improve estimates of ET by allowing the modelled upper-layer soil moisture to more closely match the pulse precipitation dynamics of these semi-arid ecosystems; however, the partitioning of T from E is not solved by this modification alone.

The upright posture imposes a significant challenge to blood pressure regulation that is compensated through baroreflex-mediated increases in heart rate and vascular resistance. Orthostatic cardiac responses are easily inferred from heart rate, but vascular resistance responses are harder to elucidate. One approach is to determine vascular resistance as arterial pressure/blood flow, where blood flow is inferred from ultrasound-based measurements of brachial blood velocity. This relies on the as yet unvalidated assumption that brachial artery diameter does not change during orthostatic stress, and so velocity is proportional to flow. It is also unknown whether the orthostatic vascular resistance response is related to initial blood vessel diameter. We determined beat-to-beat heart rate (ECG), blood pressure (Portapres) and vascular resistance (Doppler ultrasound) during a combined orthostatic stress test (head-upright tilting and lower body negative pressure) continued until presyncope. Participants were 16 men (aged 38.4±2.3 years) who lived permanently at high altitude (4450m). The supine brachial diameter ranged from 2.9-5.6mm. Brachial diameter did not change during orthostatic stress (supine: 4.19±0.2mm; tilt: 4.20±0.2mm; -20mmHg lower body negative pressure: 4.19±0.2mm, p = 0.811). There was no significant correlation between supine brachial artery diameter and the maximum vascular resistance response (r = 0.323; p = 0.29). Forearm vascular resistance responses evaluated using brachial arterial flow and velocity were strongly correlated (r = 0.989, p<0.00001) and demonstrated high equivalency with minimal bias (-6.34±24.4%). During severe orthostatic stress the diameter of the brachial artery remains constant, supporting use of brachial velocity for accurate continuous non-invasive orthostatic vascular resistance responses. The magnitude of the orthostatic forearm vascular resistance response was unrelated to the baseline brachial arterial diameter, suggesting that upstream vessel size does not matter in the ability to mount a vasoconstrictor response to orthostasis.