Environmental controls on the light use efficiency of terrestrial gross primary production

Gross primary production (GPP) by terrestrial ecosystems is a key quantity in the global carbon cycle. The instantaneous controls of leaf-level photosynthesis are well established, but there is still no consensus on the mechanisms by which canopy-level GPP depends on spatial and temporal variation in the environment. The standard model of photosynthesis provides a robust mechanistic representation for C3 species; however, additional assumptions are required to “scale up” from leaf to canopy. As a consequence, competing models make inconsistent predictions about how GPP will respond to continuing environmental change. This problem is addressed here by means of an empirical analysis of the light use efficiency (LUE) of GPP inferred from eddy covariance carbon dioxide flux measurements, in situ measurements of photosynthetically active radiation (PAR), and remotely sensed estimates of the fraction of PAR (fAPAR) absorbed by the vegetation canopy. Focusing on LUE allows potential drivers of GPP to be separated from its overriding dependence on light. GPP data from over 100 sites, collated over 20 years and located in a range of biomes and climate zones, were extracted from the FLUXNET2015 database and combined with remotely sensed fAPAR data to estimate daily LUE. Daytime air temperature, vapor pressure deficit, diffuse fraction of solar radiation, and soil moisture were shown to be salient predictors of LUE in a generalized linear mixed-effects model. The same model design was fitted to site-based LUE estimates generated by 16 terrestrial ecosystem models. The published models showed wide variation in the shape, the strength, and even the sign of the environmental effects on modeled LUE. These findings highlight important model deficiencies and suggest a need to progress beyond simple “goodness of fit” comparisons of inferred and predicted carbon fluxes toward an approach focused on the functional responses of the underlying dependencies

A unifying conceptual model for the environmental responses of isoprene emissions from plants

This is the final version of the article. Available from the publisher via the DOI in this record.BACKGROUND AND AIMS: Isoprene is the most important volatile organic compound emitted by land plants in terms of abundance and environmental effects. Controls on isoprene emission rates include light, temperature, water supply and CO2 concentration. A need to quantify these controls has long been recognized. There are already models that give realistic results, but they are complex, highly empirical and require separate responses to different drivers. This study sets out to find a simpler, unifying principle. METHODS: A simple model is presented based on the idea of balancing demands for reducing power (derived from photosynthetic electron transport) in primary metabolism versus the secondary pathway that leads to the synthesis of isoprene. This model's ability to account for key features in a variety of experimental data sets is assessed. KEY RESULTS: The model simultaneously predicts the fundamental responses observed in short-term experiments, namely: (1) the decoupling between carbon assimilation and isoprene emission; (2) a continued increase in isoprene emission with photosynthetically active radiation (PAR) at high PAR, after carbon assimilation has saturated; (3) a maximum of isoprene emission at low internal CO2 concentration (ci) and an asymptotic decline thereafter with increasing ci; (4) maintenance of high isoprene emissions when carbon assimilation is restricted by drought; and (5) a temperature optimum higher than that of photosynthesis, but lower than that of isoprene synthase activity. CONCLUSIONS: A simple model was used to test the hypothesis that reducing power available to the synthesis pathway for isoprene varies according to the extent to which the needs of carbon assimilation are satisfied. Despite its simplicity the model explains much in terms of the observed response of isoprene to external drivers as well as the observed decoupling between carbon assimilation and isoprene emission. The concept has the potential to improve global-scale modelling of vegetation isoprene emission.We thank Karena McKinney for providing the original isoprene data for the Harvard forest site. We thank Russell Monson and Ru¨diger Grote for their helpful and constructive comments on the manuscript. C.M. and I.C.P. have received funding from the European Community’s Seventh Framework Programme (FP7 2007 – 2013) under grant agreement no. 238366

Global datasets of leaf photosynthetic capacity for ecological and earth system research

The maximum rate of Rubisco carboxylation (Vcmax) determines leaf photosynthetic capacity and is a key parameter for estimating the terrestrial carbon cycle, but its spatial information is lacking, hindering global ecological research. Here, we convert leaf chlorophyll content (LCC) retrieved from satellite data to Vcmax, based on plants’ optimal distribution of nitrogen between light harvesting and carboxylation pathways. We also derive Vcmax from satellite (GOME-2) observations of sun-induced chlorophyll fluorescence (SIF) as a proxy of leaf photosynthesis using a data assimilation technique. These two independent global Vcmax products agree well (r 2=0.79, RMSE=15.46 μmol m-2 s -1 25 , P<0.001) and compare well with 3672 ground-based measurements (r2=0.68, RMSE=13.55 μmol m-2 s -1 and P<0.001 for SIF; r2=0.55, RMSE=17.55 μmol m-2 s -1 and P<0.001 for LCC). The LCC-derived Vcmax product is also used to constrain the retrieval of Vcmax from TROPOMI SIF data to produce an optimized Vcmax product using both SIF and LCC information. The global distributions of these products are compatible with Vcmax computed from an ecological optimality theory using meteorological variables, but importantly reveal additional information on the influence of land cover, irrigation, soil pH and leaf nitrogen on leaf photosynthetic capacity. These satellite-based approaches and spatial Vcmax products are primed to play a major role in global ecosystem research. The three remote sensing Vcmax products based on SIF, LCC and SIF+LCC are available at https://doi.org/10.5281/zenodo.6466968 (Chen et al., 2020) and the code for implementing the ecological optimality theory is available at https://github.com/SmithEcophysLab/optimal_vcmax_R (Smith, 2020)

Reduced streamflow in water-stressed climates consistent with CO2 effects on vegetation

Global environmental change has implications for the spatial and temporal distribution of water resources, but quantifying its effects remains a challenge. The impact of vegetation responses to increasing atmospheric CO2 concentrations on the hydrologic cycle is particularly poorly constrained1, 2, 3. Here we combine remotely sensed normalized difference vegetation index (NDVI) data and long-term water-balance evapotranspiration (ET) measurements from 190 unimpaired river basins across Australia during 1982–2010 to show that the precipitation threshold for water limitation of vegetation cover has significantly declined during the past three decades, whereas sub-humid and semi-arid basins are not only ‘greening’ but also consuming more water, leading to significant (24–28%) reductions in streamflow. In contrast, wet and arid basins show nonsignificant changes in NDVI and reductions in ET. These observations are consistent with expected effects of elevated CO2 on vegetation. They suggest that projected future decreases in precipitation4 are likely to be compounded by increased vegetation water use, further reducing streamflow in water-stressed regions

Effects of computerised clinical decision support systems (CDSS) on nursing and allied health professional performance and patient outcomes: a systematic review of experimental and observational studies

Objective Computerised clinical decision support systems (CDSS) are an increasingly important part of nurse and allied health professional (AHP) roles in delivering healthcare. The impact of these technologies on these health professionals’ performance and patient outcomes has not been systematically reviewed. We aimed to conduct a systematic review to investigate this. Materials and methods The following bibliographic databases and grey literature sources were searched by an experienced Information Professional for published and unpublished research from inception to February 2021 without language restrictions: MEDLINE (Ovid), Embase Classic+Embase (Ovid), PsycINFO (Ovid), HMIC (Ovid), AMED (Allied and Complementary Medicine) (Ovid), CINAHL (EBSCO), Cochrane Central Register of Controlled Trials (Wiley), Cochrane Database of Systematic Reviews (Wiley), Social Sciences Citation Index Expanded (Clarivate), ProQuest Dissertations & Theses Abstracts & Index, ProQuest ASSIA (Applied Social Science Index and Abstract), Clinical Trials.gov, WHO International Clinical Trials Registry (ICTRP), Health Services Research Projects in Progress (HSRProj), OpenClinical(www.OpenClinical.org), OpenGrey (www.opengrey.eu), Health.IT.gov, Agency for Healthcare Research and Quality (www.ahrq.gov). Any comparative research studies comparing CDSS with usual care were eligible for inclusion. Results A total of 36 106 non-duplicate records were identified. Of 35 included studies: 28 were randomised trials, three controlled-before-and-after studies, three interrupted-time-series and one non-randomised trial. There were ~1318 health professionals and ~67 595 patient participants in the studies. Most studies focused on nurse decision-makers (71%) or paramedics (5.7%). CDSS as a standalone Personal Computer/LAPTOP-technology was a feature of 88.7% of the studies; only 8.6% of the studies involved ‘smart’ mobile/handheld-technology. Discussion CDSS impacted 38% of the outcome measures used positively. Care processes were better in 47% of the measures adopted; examples included, nurses’ adherence to hand disinfection guidance, insulin dosing, on-time blood sampling and documenting care. Patient care outcomes in 40.7% of indicators were better; examples included, lower numbers of falls and pressure ulcers, better glycaemic control, screening of malnutrition and obesity and triaging appropriateness. Conclusion CDSS may have a positive impact on selected aspects of nurses’ and AHPs’ performance and care outcomes. However, comparative research is generally low quality, with a wide range of heterogeneous outcomes. After more than 13 years of synthesised research into CDSS in healthcare professions other than medicine, the need for better quality evaluative research remains as pressing

The importance of interacting climate modes on Australia’s contribution to global carbon cycle extremes

The global carbon cycle is highly sensitive to climate-driven fluctuations of precipitation, especially in the Southern Hemisphere. This was clearly manifested by a 20% increase of the global terrestrial C sink in 2011 during the strongest sustained La Niña since 1917. However, inconsistencies exist between El Niño/La Niña (ENSO) cycles and precipitation in the historical record; for example, significant ENSO-precipitation correlations were present in only 31% of the last 100 years, and often absent in wet years. To resolve these inconsistencies, we used an advanced temporal scaling method for identifying interactions amongst three key climate modes (El Niño, the Indian Ocean dipole, and the southern annular mode). When these climate modes synchronised (1999-2012), drought and extreme precipitation were observed across Australia. The interaction amongst these climate modes, more than the effect of any single mode, was associated with large fluctuations in precipitation and productivity. The long-term exposure of vegetation to this arid environment has favoured a resilient flora capable of large fluctuations in photosynthetic productivity and explains why Australia was a major contributor not only to the 2011 global C sink anomaly but also to global reductions in photosynthetic C uptake during the previous decade of drought

Australian vegetation phenology: new insights from satellite remote sensing and digital repeat photography

Abstract. Phenology is the study of periodic biological occurrences and can provide important insights into the influence of climatic variability and change on ecosystems. Understanding Australia’s vegetation phenology is a challenge due to its diverse range of ecosystems, from savannas and tropical rainforests to temperate eucalypt woodlands, semi-arid scrublands and alpine grasslands. These ecosystems exhibit marked differences in seasonal patterns of canopy development and plant life-cycle events, much of which deviates from the predictable seasonal phenological pulse of temperate deciduous and boreal biomes. Many Australian ecosystems are subject to irregular events (i.e., drought, flooding, cyclones and fire) that can alter ecosystem composition, structure and functioning just as much as seasonal change. We show how satellite remote sensing and ground-based digital repeat photography (i.e. phenocams) can be used to improve understanding of phenology in Australian ecosystems. First, we examine temporal variation in phenology at the continental scale using the Enhanced Vegetation Index (EVI), calculated from MODerate resolution Imaging Spectroradiomter (MODIS) data. Spatial gradients are revealed, ranging from regions with pronounced seasonality in canopy development (i.e., tropical savannas) to regions where seasonal variation is minimal (i.e., tropical rainforests) or high but irregular (i.e., arid ecosystems). Next, we use time series colour information extracted from phenocam imagery to illustrate a range of phenological signals in four contrasting Australian ecosystems. These include greening and senescing events in tropical savannas and temperate eucalypt understory, as well as strong seasonal dynamics of individual trees in a seemingly static evergreen rainforest. We also demonstrate how phenology links with ecosystem gross primary productivity (from eddy covariance) and discuss why these processes are linked in some ecosystems but not others. We conclude that phenocams have the potential to greatly improve current understanding of Australian ecosystems. To facilitate sharing of this information, we have formed the Australian Phenocam Network (http://phenocam.org.au/). </jats:p

Reviews and syntheses: Australian vegetation phenology: New insights from satellite remote sensing and digital repeat photography

Phenology is the study of periodic biological occurrences and can provide important insights into the influence of climatic variability and change on ecosystems. Understanding Australia's vegetation phenology is a challenge due to its diverse range of ecosystems, from savannas and tropical rainforests to temperate eucalypt woodlands, semiarid scrublands, and alpine grasslands. These ecosystems exhibit marked differences in seasonal patterns of canopy development and plant life-cycle events, much of which deviates from the predictable seasonal phenological pulse of temperate deciduous and boreal biomes. Many Australian ecosystems are subject to irregular events (i.e. drought, flooding, cyclones, and fire) that can alter ecosystem composition, structure, and functioning just as much as seasonal change. We show how satellite remote sensing and ground-based digital repeat photography (i.e. phenocams) can be used to improve understanding of phenology in Australian ecosystems. First, we examine temporal variation in phenology on the continental scale using the enhanced vegetation index (EVI), calculated from MODerate resolution Imaging Spectroradiometer (MODIS) data. Spatial gradients are revealed, ranging from regions with pronounced seasonality in canopy development (i.e. tropical savannas) to regions where seasonal variation is minimal (i.e. tropical rainforests) or high but irregular (i.e. arid ecosystems). Next, we use time series colour information extracted from phenocam imagery to illustrate a range of phenological signals in four contrasting Australian ecosystems. These include greening and senescing events in tropical savannas and temperate eucalypt understorey, as well as strong seasonal dynamics of individual trees in a seemingly static evergreen rainforest. We also demonstrate how phenology links with ecosystem gross primary productivity (from eddy covariance) and discuss why these processes are linked in some ecosystems but not others. We conclude that phenocams have the potential to greatly improve the current understanding of Australian ecosystems. To facilitate the sharing of this information, we have formed the Australian Phenocam Network (http://phenocam.org.au/)

Reconciling global-model estimates and country reporting of anthropogenic forest CO2 sinks

This is the author accepted manuscript. The final version is available from Springer Nature via the DOI in this recordData availability: The data that support the findings of this study are available from the corresponding author upon request.Achieving the long-term temperature goal of the Paris Agreement requires forest-based mitigation. Collective progress towards this goal will be assessed by the Paris Agreement’s Global stocktake. At present, there is a discrepancy of about 4 GtCO2yr−1in global anthropogenic net land-use emissions between global models (reflected in IPCC assessment reports) and aggregated national GHG inventories (under the UNFCCC). We show that a substantial part of this discrepancy (about 3.2 GtCO2yr−1) can be explained by conceptual differences in anthropogenic forest sink estimation, related to the representation of environmental change impacts and the areas considered as managed. For a more credible tracking of collective progress under the Global stocktake, these conceptual differences between models and inventories need to be reconciled. We implement a new method of disaggregation of global land model results that allows greater comparability with GHG inventories. This provides a deeper understanding of model–inventory differences, allowing more transparent analysis of forest-based mitigation and facilitating a more accurate Global stocktake.J.H. was supported by EU FP7 through project LUC4C (GA603542) and the UK NERC project GGRiLS-GAP. G.G. was supported by Administrative Arrangement Number 340203/2016/742550/SER/CLIMA.A3. A.K.J. was supported by the NSF (AGS 12-43071) and DOE (DE-SC0016323). J.E.M.S.N. was supported by the German Research Foundation’s Emmy Noether Programme (grant number PO1751/1-1). G.G., J.H., G.P.P. and L.P. received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement number 776810 (VERIFY). C.D.K. was supported by the US DOE under Contract DE-AC02-05CH11231 as part of their RGMA (BGC-Feedbacks SFA) and TES Programs (NGEE-Tropics). A.K.J. was supported under the US NSF (NSF-AGS-12-43071)

A trade-off between plant and soil carbon storage under elevated CO2

This is the author accepted manuscript. The final version is available from Nature Research via the DOI in this record.Data availability: All the empirical data that support the main findings of this study have been deposited in Figshare: (https://figshare.com/account/home#/projects/74721) and GitHub (https://github.com/cesarterrer/SoilC_CO2). FACE-MDS data can be accessed at https://www.osti.gov/dataexplorer/biblio/dataset/1480327. CMIP5 data can be accessed at https://esgf-index1.ceda.ac.uk/search/cmip5-ceda/. TRENDY data can be requested at http://dgvm.ceh.ac.uk/index.html.Code availability: The R code used in the analysis presented in this paper is available in GitHub and can be accessed at https://github.com/cesarterrer/SoilC_CO2Terrestrial ecosystems remove about 30% of the CO2 emitted by human activities each year, yet the persistence of this carbon sink partly depends on how plant biomass and soil carbon stocks respond to future increases in atmospheric CO2. While plant biomass often increases in elevated CO2 (eCO2) experiments, soil carbon has been observed to increase, remain unchanged, or even decline. The mechanisms driving this variation across experiments remain poorly understood, creating uncertainty in climate projections. Here, we synthesized data from 108 eCO2 experiments and found that the effect of eCO2 on soil carbon stocks is best explained by a negative relationship with plant biomass: when plant biomass is strongly stimulated by eCO2, soil carbon accrual declines; conversely, when biomass is weakly stimulated, soil carbon accumulates. This trade-off appears related to plant nutrient acquisition, whereby enhanced biomass requires mining the soil for nutrients, which decreases soil carbon accrual. We found an increase in soil carbon stocks with eCO2 in grasslands (8±2%) and no increase in forests (0±2%), even though plant biomass in grassland responded less strongly (9±3%) than in forest (23±2%). Ecosystem models do not reproduce this trade-off, which implies that projections of soil carbon may need to be revised.Lawrence Livermore National Laboratory (LLNL).U.S. Department of Energy, Terrestrial Ecosystem Science ProgramNAS