Networking the forest infrastructure towards near real-time monitoring - A white paper.

Forests account for nearly 90 % of the world's terrestrial biomass in the form of carbon and they support 80 % of the global biodiversity. To understand the underlying forest dynamics, we need a long-term but also relatively high-frequency, networked monitoring system, as traditionally used in meteorology or hydrology. While there are numerous existing forest monitoring sites, particularly in temperate regions, the resulting data streams are rarely connected and do not provide information promptly, which hampers real-time assessments of forest responses to extreme climate events. The technology to build a better global forest monitoring network now exists. This white paper addresses the key structural components needed to achieve a novel meta-network. We propose to complement - rather than replace or unify - the existing heterogeneous infrastructure with standardized, quality-assured linking methods and interacting data processing centers to create an integrated forest monitoring network. These automated (research topic-dependent) linking methods in atmosphere, biosphere, and pedosphere play a key role in scaling site-specific results and processing them in a timely manner. To ensure broad participation from existing monitoring sites and to establish new sites, these linking methods must be as informative, reliable, affordable, and maintainable as possible, and should be supplemented by near real-time remote sensing data. The proposed novel meta-network will enable the detection of emergent patterns that would not be visible from isolated analyses of individual sites. In addition, the near real-time availability of data will facilitate predictions of current forest conditions (nowcasts), which are urgently needed for research and decision making in the face of rapid climate change. We call for international and interdisciplinary efforts in this direction.

Non-photochemical quenching estimates from in situ spectroradiometer measurements: implications on remote sensing of sun-induced chlorophyll fluorescence in lakes.

Quantum yield of fluorescence (ϕF) is key to interpret remote measurements of sun-induced fluorescence (SIF), and whether the SIF signal is governed by photochemical quenching (PQ) or non-photochemical quenching (NPQ). Disentangling PQ from NPQ allows using SIF estimates in various applications in aquatic optics. However, obtaining ϕF is challenging due to its high temporal and physiological variability, and the combined measurements needed to enclose all relevant optical paths. In inland waters, this type of data is scarce and information on diurnal and seasonal ϕF dynamics are almost unknown. Using an autonomous hyperspectral Thetis profiler in Lake Geneva, we demonstrate how to estimate ϕF using an ensemble of in-situ measurements acquired between 2018 to 2021. We use vertical and temporal changes in retrieved ϕF to determine NPQ and PQ conditions. We observed NPQ in 36% of the total daytime profiles used in the ϕF analysis. While downwelling irradiance is a significant contributor to ϕF, its role cannot be easily interpreted. Other factors such as phytoplankton photoregulation and assemblages also likely play significant roles in quenching mechanisms. We conclude that an adapted approach exploiting in-situ data is suitable to determine diurnal and seasonal NPQ occurrence, and helps develop future remote sensing algorithms.

Multi-sensor spectral synergies for crop stress detection and monitoring in the optical domain: A review.

Remote detection and monitoring of the vegetation responses to stress became relevant for sustainable agriculture. Ongoing developments in optical remote sensing technologies have provided tools to increase our understanding of stress-related physiological processes. Therefore, this study aimed to provide an overview of the main spectral technologies and retrieval approaches for detecting crop stress in agriculture. Firstly, we present integrated views on: i) biotic and abiotic stress factors, the phases of stress, and respective plant responses, and ii) the affected traits, appropriate spectral domains and corresponding methods for measuring traits remotely. Secondly, representative results of a systematic literature analysis are highlighted, identifying the current status and possible future trends in stress detection and monitoring. Distinct plant responses occurring under shortterm, medium-term or severe chronic stress exposure can be captured with remote sensing due to specific light interaction processes, such as absorption and scattering manifested in the reflected radiance, i.e. visible (VIS), near infrared (NIR), shortwave infrared, and emitted radiance, i.e. solar-induced fluorescence and thermal infrared (TIR). From the analysis of 96 research papers, the following trends can be observed: increasing usage of satellite and unmanned aerial vehicle data in parallel with a shift in methods from simpler parametric approaches towards more advanced physically-based and hybrid models. Most study designs were largely driven by sensor availability and practical economic reasons, leading to the common usage of VIS-NIR-TIR sensor combinations. The majority of reviewed studies compared stress proxies calculated from single-source sensor domains rather than using data in a synergistic way. We identified new ways forward as guidance for improved synergistic usage of spectral domains for stress detection: (1) combined acquisition of data from multiple sensors for analysing multiple stress responses simultaneously (holistic view); (2) simultaneous retrieval of plant traits combining multi-domain radiative transfer models and machine learning methods; (3) assimilation of estimated plant traits from distinct spectral domains into integrated crop growth models. As a future outlook, we recommend combining multiple remote sensing data streams into crop model assimilation schemes to build up Digital Twins of agroecosystems, which may provide the most efficient way to detect the diversity of environmental and biotic stresses and thus enable respective management decisions.

Satellite data reveal differential responses of Swiss forests to unprecedented 2018 drought.

Extreme events such as the summer drought of 2018 in Central Europe are projected to occur more frequently in the future and may cause major damages including increased tree mortality and negative impacts on forest ecosystem services. Here, we quantify the response of >1 million forest pixels of 10 × 10 m across Switzerland to the 2018 drought in terms of resistance, recovery, and resilience. We used the Normalized Difference Water Index (NDWI) derived from Sentinel-2 satellite data as a proxy for canopy water content and analyzed its relative change. We calculated NDWI change between the 2017 pre-drought and 2018 drought years (indicating resistance), 2018 and the 2019 post-drought (indicating recovery), and between 2017-2019 (indicating resilience). Analyzing the data from this large natural experiment, we found that for 4.3% of the Swiss forest the NDWI declined between 2017 and 2018, indicating areas with low resistance of the forest canopy to drought effects. While roughly 50% of this area recovered, in 2.7% of the forested area NDWI continued to decline from 2018 to 2019, suggesting prolonged negative effects or delayed damage. We found differential forest responses to drought associated with site topographic characteristics and forest stand characteristics, and to a lesser extent with climatic conditions and interactions between these drivers. Low drought resistance and high recovery were most prominent at forest edges, but also on south-facing slopes and lower elevations. Tree functional type was the most important driver of drought resilience, with most of the damage in stands with high conifer abundance. Our results demonstrate the suitability of satellite-based quantification of drought-induced forest damage at high spatial resolution across large areas. Such information is important to predict how local site characteristics may impact forest vulnerability to future extreme events and help in the search for appropriate adaptation strategies.

Spinal Versus General Anesthesia for Holmium Laser Enucleation of the Prostate of High-risk Patients - A Propensity-score-matched-analysis.

OBJECTIVE: To compare perioperative management and functional outcome of spinal anesthesia (SpA) to general anesthesia (GA) in high-risk patients treated for lower urinary tract symptoms with Holmium laser enucleation of the prostate (HoLEP). METHODS: In the current retrospective analysis, a propensity-score-matching of patients treated for lower urinary tract symptom with HoLEP (n = 300) in SpA with ASA>2 (n = 100), GA with ASA>2 (GA-high-risk) (n = 100) or GA with ASA≤2 (GA-low-risk) (n = 100) was performed. The impact of anesthesiologic mode on perioperative anesthesiologic outcome, early functional outcome and treatment related adverse events (according to Clavien Dindo), was evaluated. RESULTS: Hypotensive episodes were significantly less frequent in the SpA-cohort (9%) compared to the GA-high-risk cohort (32%) and the GA low-risk cohort (22%) (each P <.05 respectively). SpA-patients showed a significantly shorter median time in post anesthesia care unit (PACU-time: 135 minutes; 120-166.5) compared to GA-high-risk patients (186 minutes; 154-189.5), with significant less referrals to Intermediate care unit (1% vs 9 %); (each P <.05). PACU-time (99 minutes) and Intermediate care unit referrals (0%) for GA-low-risk were lower than for both other cohorts. Postoperative requirement for analgesics was significantly lower in the SpA-cohort (2%), compared to both GA-cohorts (74% and 61% respectively; P <.05). No significant difference was found regarding early functional outcome or treatment related adverse events (p-range: 0.201-1.000). CONCLUSION: For patients undergoing HoLEP, SpA provides greater hemodynamic stability and allows faster overall postoperative recovery with preferable pain management. Yielding a comparable functional outcome, it is a safe and efficient alternative to GA in high-risk patients.

Downscaling of far-red solar-induced chlorophyll fluorescence of different crops from canopy to leaf level using a diurnal data set acquired by the airborne imaging spectrometer HyPlant.

Remote sensing-based measurements of solar-induced chlorophyll fluorescence (SIF) are useful for assessing plant functioning at different spatial and temporal scales. SIF is the most direct measure of photosynthesis and is therefore considered important to advance capacity for the monitoring of gross primary production (GPP) while it has also been suggested that its yield facilitates the early detection of vegetation stress. However, due to the influence of different confounding effects, the apparent SIF signal measured at canopy level differs from the fluorescence emitted at leaf level, which makes its physiological interpretation challenging. One of these effects is the scattering of SIF emitted from leaves on its way through the canopy. The escape fraction ( f esc ) describes the scattering of SIF within the canopy and corresponds to the ratio of apparent SIF at canopy level to SIF at leaf level. In the present study, the fluorescence correction vegetation index (FCVI) was used to determine f esc of far-red SIF for three structurally different crops (sugar beet, winter wheat, and fruit trees) from a diurnal data set recorded by the airborne imaging spectrometer HyPlant. This unique data set, for the first time, allowed a joint analysis of spatial and temporal dynamics of structural effects and thus the downscaling of far-red SIF from canopy ( SIF 760 canopy ) to leaf level ( SIF 760 leaf ). For a homogeneous crop such as winter wheat, it seems to be sufficient to determine f esc once a day to reliably scale SIF760 from canopy to leaf level. In contrast, for more complex canopies such as fruit trees, calculating f esc for each observation time throughout the day is strongly recommended. The compensation for structural effects, in combination with normalizing SIF760 to remove the effect of incoming radiation, further allowed the estimation of SIF emission efficiency ( ε SIF ) at leaf level, a parameter directly related to the diurnal variations of plant photosynthetic efficiency.

The BDNFVal66Met SNP modulates the association between beta-amyloid and hippocampal disconnection in Alzheimer's disease.

In Alzheimer's disease (AD), a single-nucleotide polymorphism in the gene encoding brain-derived neurotrophic factor (BDNFVal66Met) is associated with worse impact of primary AD pathology (beta-amyloid, Aß) on neurodegeneration and cognitive decline, rendering BDNFVal66Met an important modulating factor of cognitive impairment in AD. However, the effect of BDNFVal66Met on functional networks that may underlie cognitive impairment in AD is poorly understood. Using a cross-validation approach, we first explored in subjects with autosomal dominant AD (ADAD) from the Dominantly Inherited Alzheimer Network (DIAN) the effect of BDNFVal66Met on resting-state fMRI assessed functional networks. In seed-based connectivity analysis of six major large-scale networks, we found a stronger decrease of hippocampus (seed) to medial-frontal connectivity in the BDNFVal66Met carriers compared to BDNFVal homozogytes. BDNFVal66Met was not associated with connectivity in any other networks. Next, we tested whether the finding of more pronounced decrease in hippocampal-medial-frontal connectivity in BDNFVal66Met could be also found in elderly subjects with sporadically occurring Aß, including a group with subjective cognitive decline (N = 149, FACEHBI study) and a group ranging from preclinical to AD dementia (N = 114, DELCODE study). In both of these independently recruited groups, BDNFVal66Met was associated with a stronger effect of more abnormal Aß-levels (assessed by biofluid-assay or amyloid-PET) on hippocampal-medial-frontal connectivity decreases, controlled for hippocampus volume and other confounds. Lower hippocampal-medial-frontal connectivity was associated with lower global cognitive performance in the DIAN and DELCODE studies. Together these results suggest that BDNFVal66Met is selectively associated with a higher vulnerability of hippocampus-frontal connectivity to primary AD pathology, resulting in greater AD-related cognitive impairment.

Remote sensing of forest gas exchange: Considerations derived from a tomographic perspective.

The global exchange of gas (CO2 , H2 O) and energy (sensible and latent heat) between forest ecosystems and the atmosphere is often assessed using remote sensing (RS) products. Although these products are essential in quantifying the spatial variability of forest-atmosphere exchanges, large uncertainties remain from a measurement bias towards top of canopy fluxes since optical RS data are not sensitive for the vertically integrated forest canopy. We hypothesize that a tomographic perspective opens new pathways to advance upscaling gas exchange processes from leaf to forest stands and larger scales. We suggest a 3D modelling environment comprising principles of ecohydrology and radiative transfer modelling with measurements of micrometeorological variables, leaf optical properties and forest structure, and assess 3D fields of net CO2 assimilation (An ) and transpiration (T) in a Swiss temperate forest canopy. 3D simulations were used to quantify uncertainties in gas exchange estimates inherent to RS approaches and model assumptions (i.e. a big-leaf approximation in modelling approaches). Our results reveal substantial 3D heterogeneity of forest gas exchange with top of canopy An and T being reduced by up to 98% at the bottom of the canopy. We show that a simplified use of RS causes uncertainties in estimated vertical gas exchange of up to 300% and that the spatial variation of gas exchange in the footprint of flux towers can exceed diurnal dynamics. We also demonstrate that big-leaf assumptions can cause uncertainties up to a factor of 10 for estimates of An and T. Concluding, we acknowledge the large potential of 3D assessments of gas exchange to unravelling the role of vertical variability and canopy structure in regulating forest-atmosphere gas and energy exchange. Such information allows to systematically link canopy with global scale controls on forest functioning and eventually enables advanced understanding of forest responses to environmental change.

Ecosystem service change caused by climatological and non-climatological drivers: a Swiss case study.

Understanding the drivers of ecosystem change and their effects on ecosystem services are essential for management decisions and verification of progress towards national and international sustainability policies (e.g., Aichi Biodiversity Targets, Sustainable Development Goals). We aim to disentangle spatially the effect of climatological and non-climatological drivers on ecosystem service supply and trends. Therefore, we explored time series of three ecosystem services in Switzerland between 2004 and 2014: carbon dioxide regulation, soil erosion prevention, and air quality regulation. We applied additive models to describe the spatial variation attributed to climatological (i.e., temperature, precipitation and relative sunshine duration) and non-climatological drivers (i.e., random effects representing other spatially structured processes) that may affect ecosystem service change. Obtained results indicated strong influences of climatological drivers on ecosystem service trends in Switzerland. We identified equal contributions of all three climatological drivers on trends of carbon dioxide regulation and soil erosion prevention, while air quality regulation was more strongly influenced by temperature. Additionally, our results showed that climatological and non-climatological drivers affected ecosystem services both negatively and positively, depending on the regions (in particular lower and higher altitudinal areas), drivers, and services assessed. Our findings highlight stronger effects of climatological compared to non-climatological drivers on ecosystem service change in Switzerland. Furthermore, drivers of ecosystem change display a spatial heterogeneity in their influence on ecosystem service trends. We propose an approach building on an additive model to disentangle the effect of climatological and non-climatological drivers on ecosystem service trends. Such analyses should be extended in the future to ecosystem service flow and demand to complete ecosystem service assessments and to demonstrate and communicate more clearly the benefits of ecosystem services for human well-being.

Functional connectivity associated with tau levels in ageing, Alzheimer's, and small vessel disease.

In Alzheimer's disease, tau pathology spreads hierarchically from the inferior temporal lobe throughout the cortex, ensuing cognitive decline and dementia. Similarly, circumscribed patterns of pathological tau have been observed in normal ageing and small vessel disease, suggesting a spatially ordered distribution of tau pathology across normal ageing and different diseases. In vitro findings suggest that pathological tau may spread 'prion-like' across neuronal connections in an activity-dependent manner. Supporting this notion, functional brain networks show a spatial correspondence to tau deposition patterns. However, it remains unclear whether higher network-connectivity facilitates tau propagation. To address this, we included 55 normal aged elderly (i.e. cognitively normal, amyloid-negative), 50 Alzheimer's disease patients (i.e. amyloid-positive) covering the preclinical to dementia spectrum, as well as 36 patients with pure (i.e. amyloid-negative) vascular cognitive impairment due to small vessel disease. All subjects were assessed with AV1451 tau-PET and resting-state functional MRI. Within each group, we computed atlas-based resting-state functional MRI functional connectivity across 400 regions of interest covering the entire neocortex. Using the same atlas, we also assessed within each group the covariance of tau-PET levels among the 400 regions of interest. We found that higher resting-state functional MRI assessed functional connectivity between any given region of interest pair was associated with higher covariance in tau-PET binding in corresponding regions of interest. This result was consistently found in normal ageing, Alzheimer's disease and vascular cognitive impairment. In particular, inferior temporal tau-hotspots, as defined by highest tau-PET uptake, showed high predictive value of tau-PET levels in functionally closely connected regions of interest. These associations between functional connectivity and tau-PET uptake were detected regardless of presence of dementia symptoms (mild cognitive impairment or dementia), amyloid deposition (as assessed by amyloid-PET) or small vessel disease. Our findings suggest that higher functional connectivity between brain regions is associated with shared tau-levels, supporting the view of prion-like tau spreading facilitated by neural activity.

Remote sensing of solar-induced chlorophyll fluorescence (SIF) in vegetation: 50 years of progress.

Remote sensing of solar-induced chlorophyll fluorescence (SIF) is a rapidly advancing front in terrestrial vegetation science, with emerging capability in space-based methodologies and diverse application prospects. Although remote sensing of SIF - especially from space - is seen as a contemporary new specialty for terrestrial plants, it is founded upon a multi-decadal history of research, applications, and sensor developments in active and passive sensing of chlorophyll fluorescence. Current technical capabilities allow SIF to be measured across a range of biological, spatial, and temporal scales. As an optical signal, SIF may be assessed remotely using highly-resolved spectral sensors and state-of-the-art algorithms to distinguish the emission from reflected and/or scattered ambient light. Because the red to far-red SIF emission is detectable non-invasively, it may be sampled repeatedly to acquire spatio-temporally explicit information about photosynthetic light responses and steady-state behaviour in vegetation. Progress in this field is accelerating with innovative sensor developments, retrieval methods, and modelling advances. This review distills the historical and current developments spanning the last several decades. It highlights SIF heritage and complementarity within the broader field of fluorescence science, the maturation of physiological and radiative transfer modelling, SIF signal retrieval strategies, techniques for field and airborne sensing, advances in satellite-based systems, and applications of these capabilities in evaluation of photosynthesis and stress effects. Progress, challenges, and future directions are considered for this unique avenue of remote sensing.

Variability of sun-induced chlorophyll fluorescence according to stand age-related processes in a managed loblolly pine forest.

Leaf fluorescence can be used to track plant development and stress, and is considered the most direct measurement of photosynthetic activity available from remote sensing techniques. Red and far-red sun-induced chlorophyll fluorescence (SIF) maps were generated from high spatial resolution images collected with the HyPlant airborne spectrometer over even-aged loblolly pine plantations in North Carolina (United States). Canopy fluorescence yield (i.e., the fluorescence flux normalized by the light absorbed) in the red and far-red peaks was computed. This quantifies the fluorescence emission efficiencies that are more directly linked to canopy function compared to SIF radiances. Fluorescence fluxes and yields were investigated in relation to tree age to infer new insights on the potential of those measurements in better describing ecosystem processes. The results showed that red fluorescence yield varies with stand age. Young stands exhibited a nearly twofold higher red fluorescence yield than mature forest plantations, while the far-red fluorescence yield remained constant. We interpreted this finding in a context of photosynthetic stomatal limitation in aging loblolly pine stands. Current and future satellite missions provide global datasets of SIF at coarse spatial resolution, resulting in intrapixel mixture effects, which could be a confounding factor for fluorescence signal interpretation. To mitigate this effect, we propose a surrogate of the fluorescence yield, namely the Canopy Cover Fluorescence Index (CCFI) that accounts for the spatial variability in canopy structure by exploiting the vegetation fractional cover. It was found that spatial aggregation tended to mask the effective relationships, while the CCFI was still able to maintain this link. This study is a first attempt in interpreting the fluorescence variability in aging forest stands and it may open new perspectives in understanding long-term forest dynamics in response to future climatic conditions from remote sensing of SIF.

Sun-induced chlorophyll fluorescence from high-resolution imaging spectroscopy data to quantify spatio-temporal patterns of photosynthetic function in crop canopies.

Passive detection of sun-induced chlorophyll fluorescence (SIF) using spectroscopy has been proposed as a proxy to quantify changes in photochemical efficiency at canopy level under natural light conditions. In this study, we explored the use of imaging spectroscopy to quantify spatio-temporal dynamics of SIF within crop canopies and its sensitivity to track patterns of photosynthetic activity originating from the interaction between vegetation structure and incoming radiation as well as variations in plant function. SIF was retrieved using the Fraunhofer Line Depth (FLD) principle from imaging spectroscopy data acquired at different time scales a few metres above several crop canopies growing under natural illumination. We report the first maps of canopy SIF in high spatial resolution. Changes of SIF were monitored at different time scales ranging from quick variations under induced stress conditions to seasonal dynamics. Natural changes were primarily determined by varying levels and distribution of photosynthetic active radiation (PAR). However, this relationship changed throughout the day demonstrating an additional physiological component modulating spatio-temporal patterns of SIF emission. We successfully used detailed SIF maps to track changes in the canopy's photochemical activity under field conditions, providing a new tool to evaluate complex patterns of photosynthesis within the canopy.

Simulations of chlorophyll fluorescence incorporated into the Community Land Model version 4.

Several studies have shown that satellite retrievals of solar-induced chlorophyll fluorescence (SIF) provide useful information on terrestrial photosynthesis or gross primary production (GPP). Here, we have incorporated equations coupling SIF to photosynthesis in a land surface model, the National Center for Atmospheric Research Community Land Model version 4 (NCAR CLM4), and have demonstrated its use as a diagnostic tool for evaluating the calculation of photosynthesis, a key process in a land surface model that strongly influences the carbon, water, and energy cycles. By comparing forward simulations of SIF, essentially as a byproduct of photosynthesis, in CLM4 with observations of actual SIF, it is possible to check whether the model is accurately representing photosynthesis and the processes coupled to it. We provide some background on how SIF is coupled to photosynthesis, describe how SIF was incorporated into CLM4, and demonstrate that our simulated relationship between SIF and GPP values are reasonable when compared with satellite (Greenhouse gases Observing SATellite; GOSAT) and in situ flux-tower measurements. CLM4 overestimates SIF in tropical forests, and we show that this error can be corrected by adjusting the maximum carboxylation rate (Vmax ) specified for tropical forests in CLM4. Our study confirms that SIF has the potential to improve photosynthesis simulation and thereby can play a critical role in improving land surface and carbon cycle models.