Do we (need to) care about canopy radiation schemes in DGVMs? Caveats and potential impacts

Dynamic global vegetation models (DGVMs) are an essential part of current state-of-the-art Earth system models. In recent years, the complexity of DGVMs has increased by incorporating new important processes like, e.g., nutrient cycling and land cover dynamics, while biogeophysical processes like surface radiation have not been developed much further. Canopy radiation models are however very important for the estimation of absorption and reflected fluxes and are essential for a proper estimation of surface carbon, energy and water fluxes. The present study provides an overview of current implementations of canopy radiation schemes in a couple of state-of-the-art DGVMs and assesses their accuracy in simulating canopy absorption and reflection for a variety of different surface conditions. Systematic deviations in surface albedo and fractions of absorbed photosynthetic active radiation (faPAR) are identified and potential impacts are assessed. The results show clear deviations for both, absorbed and reflected, surface solar radiation fluxes. FaPAR is typically underestimated, which results in an underestimation of gross primary productivity (GPP) for the investigated cases. The deviation can be as large as 25% in extreme cases. Deviations in surface albedo range between −0.15 ≤ Δα ≤ 0.36, with a slight positive bias on the order of Δα ≈ 0.04. Potential radiative forcing caused by albedo deviations is estimated at −1.25 ≤ RF ≤ −0.8 (W m−2), caused by neglect of the diurnal cycle of surface albedo. The present study is the first one that provides an assessment of canopy RT schemes in different currently used DGVMs together with an assessment of the potential impact of the identified deviations. The paper illustrates that there is a general need to improve the canopy radiation schemes in DGVMs and provides different perspectives for their improvement

Application of Sentinel-2A data for pasture biomass monitoring using a physically based radiative transfer model

A large proportion of the global land surface is covered by pasture. The advent of the Sentinel satellites program provides free datasets with good spatiotemporal resolution that can be a valuable source of information for monitoring pasture resources. We combined optical remote sensing data (proximal hyperspectral and Sentinel 2A) with a radiative transfer model (PROSAIL) to estimate leaf area index (LAI), and biomass, in a dairy farming context. Three sites in Southern England were used: two pasture farms that differed in pasture type and management, and a set of small agronomy trial plots with different mixtures of grasses, legumes and herbs, as well as pure perennial ryegrass. The proximal and satellite spectral data were used to retrieve LAI via PROSAIL model inversion, which were compared against field observations of LAI. The potential of bands of Sentinel 2A that corresponded with a 10 m resolution was studied by convolving narrow spectral bands (from a handheld hyperspectral sensor) into Sentinel 2A bands (10 m). Retrieved LAI, using these spectrally resampled S2A data, compared well with measured LAI, for all sites, even for those with mixed species cover (although retrieved LAI was somewhat overestimated for pasture mixtures with high LAI). This proved the suitability of 10 m Sentinel 2A spectral bands for capturing LAI dynamics for different types of pastures. We also found that inclusion of 20 m bands in the inversion scheme did not lead to any further improvement in retrieved LAI. Sentinel 2A image based retrieval yielded good agreement with LAI measurements obtained for a typical perennial ryegrass based pasture farm. LAI retrieved in this way was used to create biomass maps (that correspond to indirect biomass measurements by Rising Plate Meter (RPM)), for mixed-species paddocks for a farm for which limited field data were available. These maps compared moderately well with farmer-collected RPM measurements for this farm. We propose that estimates of paddock-averaged and within-paddock variability of biomass are more reliably obtained from a combined Sentinel 2A-PROSAIL approach, rather than by manual RPM measurements. The physically based radiative transfer model inversion approach outperformed the Normalised Difference Vegetation Index based retrieval method, and does not require site specific calibrations of the inversion scheme

Food choice responses to changes in the price of a staple crop: a discrete choice experiment of maize in rural Malawi

Price and affordability are important drivers of food choice, particularly for rural smallholder farming households in Malawi, experiencing extreme poverty, food insecurity, and lack of dietary diversity. Lowering the cost of staple crops such as maize targeted by agricultural input subsidy programmes (AISPs) may potentially increase consumption of the staple crop, but it might also lead to consumption of a more diverse range of foods. Using a discrete choice experiment, this study investigated food choice responses to changes in maize price in rural Malawi. Study participants (n = 400) were given a series of choice tasks for which they were asked to choose between food baskets with varying cost, reflecting local prices and with maize at both high and low price. Baskets contained different types of foods including maize, rice, cabbage, small-dried fish, and/or a soft drink. The data were analysed using mixed logit models including investigation of heterogenous effects based on socio-demographic characteristics, food security and actual market purchases. Individuals revealed a preference, as expected, for lower cost food baskets. Small-dried fish and cabbage were the highest valued food products. At a low cost of maize, the expected utility from a basket with maize was greater than a basket with other items, particularly among households with high- and low-food purchases, low socioeconomic status, living in Phalombe District, and experiencing food insecurity, indicating that among such populations a low price of maize will not necessarily lead to increases in dietary diversity. In contrast, among households living in Lilongwe District, with high SES and food secure, a lower maize price will not lead to a loss in dietary diversity as they prefer a basket containing non-maize products over maize. The findings suggest that achieving food security and dietary diversity may require a range of policy approaches addressing different pathways of impact as opposed to relying on subsidizing inputs for staple crop production

Underestimation of global photosynthesis in Earth System Models due to representation of vegetation structure

The impact of vegetation structure on the absorption of shortwave radiation in Earth System Models (ESMs) is potentially important for accurate modelling of the carbon cycle and hence climate projections. A proportion of incident shortwave radiation is used by plants to photosynthesize and canopy structure has a direct impact on the fraction of this radiation which is absorbed. This paper evaluates how modelled carbon assimilation of the terrestrial biosphere is impacted when clumping derived from satellite data is incorporated. We evaluated impacts of clumping on photosynthesis using the Joint UK Land Environment Simulator, the land surface scheme of the UK Earth System Model. At the global level, Gross Primary Productivity (GPP) increased by 5.53 ± 1.02 PgC yr−1 with the strongest absolute increase in the tropics. This is contrary to previous studies that have shown a decrease in photosynthesis when similar clumping data sets have been used to modify light interception in models. In our study additional transmission of light through upper canopy layers leads to enhanced absorption in lower layers in which photosynthesis tends to be light limited. We show that this result is related to the complexity of canopy scheme being used

Seasonal pattern of regional carbon balance in the central Rocky Mountains from surface and airborne measurements

[1] High-elevation forests represent a large fraction of potential carbon uptake in North America, but this uptake is not well constrained by observations. Additionally, forests in the Rocky Mountains have recently been severely damaged by drought, fire, and insect outbreaks, which have been quantified at local scales but not assessed in terms of carbon uptake at regional scales. The Airborne Carbon in the Mountains Experiment was carried out in 2007 partly to assess carbon uptake in western U.S. mountain ecosystems. The magnitude and seasonal change of carbon uptake were quantified by (1) paired upwind-downwind airborne CO2 observations applied in a boundary layer budget, (2) a spatially explicit ecosystem model constrained using remote sensing and flux tower observations, and (3) a downscaled global tracer transport inversion. Top-down approaches had mean carbon uptake equivalent to flux tower observations at a subalpine forest, while the ecosystem model showed less. The techniques disagreed on temporal evolution. Regional carbon uptake was greatest in the early summer immediately following snowmelt and tended to lessen as the region experienced dry summer conditions. This reduction was more pronounced in the airborne budget and inversion than in flux tower or upscaling, possibly related to lower snow water availability in forests sampled by the aircraft, which were lower in elevation than the tower site. Changes in vegetative greenness associated with insect outbreaks were detected using satellite reflectance observations, but impacts on regional carbon cycling were unclear, highlighting the need to better quantify this emerging disturbance effect on montane forest carbon cycling

Probabilistic downscaling of remote sensing data with applications for multi-scale biogeochemical flux modeling

Upscaling ecological information to larger scales in space and downscaling remote sensing observations or model simulations to finer scales remain grand challenges in Earth system science. Downscaling often involves inferring subgrid information from coarse-scale data, and such ill-posed problems are classically addressed using regularization. Here, we apply two-dimensional Tikhonov Regularization (2DTR) to simulate subgrid surface patterns for ecological applications. Specifically, we test the ability of 2DTR to simulate the spatial statistics of high-resolution (4 m) remote sensing observations of the normalized difference vegetation index (NDVI) in a tundra landscape. We find that the 2DTR approach as applied here can capture the major mode of spatial variability of the high-resolution information, but not multiple modes of spatial variability, and that the Lagrange multiplier (γ) used to impose the condition of smoothness across space is related to the range of the experimental semivariogram. We used observed and 2DTR-simulated maps of NDVI to estimate landscape-level leaf area index (LAI) and gross primary productivity (GPP). NDVI maps simulated using a γ value that approximates the range of observed NDVI result in a landscape-level GPP estimate that differs by ca 2% from those created using observed NDVI. Following findings that GPP per unit LAI is lower near vegetation patch edges, we simulated vegetation patch edges using multiple approaches and found that simulated GPP declined by up to 12% as a result. 2DTR can generate random landscapes rapidly and can be applied to disaggregate ecological information and compare of spatial observations against simulated landscapes

Experience of, awareness of and help-seeking for potential cancer symptoms in smokers and non-smokers: A cross-sectional study

Background Presenting to primary care with potential cancer symptoms is contingent on one’s ability to recognize potentially serious symptoms. We investigated differences between smokers and non-smokers in symptoms experienced, awareness and consulting of potential respiratory, head and neck cancer symptoms. Methods Smokers and non-smokers aged over 50 from Yorkshire general practice lists were sent a postal questionnaire asking about symptoms, consulting and awareness of cancer symptoms. Data were analysed using STATA14. Results Response rate after one reminder was 30.5% (1205/3954). Smoking status was associated with experience of cough (p<0.001), breathlessness (p = 0.002) and tiredness (p = 0.004) with smokers (25.8% of population) more likely than never-smokers (53.6% of population) to experience all three symptoms (cough OR = 2.56;95%CI[1.75–3.75], breathlessness OR = 2.39;95%CI[1.43–4.00], tiredness OR = 1.57;95%CI[1.12–2.19]). Smoking status was associated with awareness of breathlessness as a potential cancer symptom (p = 0.035) and consulting for cough (p = 0.011) with smokers less likely to consult than never-smokers (OR = 0.37;95% CI[0.17–0.80]). Conclusion Our findings suggest that current smokers are more likely to experience cough, breathlessness and tiredness, but are less likely to consult for cough than never-smokers. To increase cancer awareness and promote consulting among smokers, innovative interventions improving symptom recognition and empowering smokers to seek help are required

Evaluation of implementation and effectiveness of digital adherence technology with differentiated care to support tuberculosis treatment adherence and improve treatment outcomes in Ethiopia: a study protocol for a cluster randomised trial.

BACKGROUND: Digital adherence technologies (DATs) are recommended to support patient-centred, differentiated care to improve tuberculosis (TB) treatment outcomes, but evidence that such technologies improve adherence is limited. We aim to implement and evaluate the effectiveness of smart pillboxes and medication labels linked to an adherence data platform, to create a differentiated care response to patient adherence and improve TB care among adult pulmonary TB participants. Our study is part of the Adherence Support Coalition to End TB (ASCENT) project in Ethiopia. METHODS/DESIGN: We will conduct a pragmatic three-arm cluster-randomised trial with 78 health facilities in two regions in Ethiopia. Facilities are randomised (1:1:1) to either of the two intervention arms or standard of care. Adults aged ≥ 18 years with drug-sensitive (DS) pulmonary TB are enrolled over 12 months and followed-up for 12 months after treatment initiation. Participants in facilities randomised to either of the two intervention arms are offered a DAT linked to the web-based ASCENT adherence platform for daily adherence monitoring and differentiated response to patient adherence for those who have missed doses. Participants at standard of care facilities receive routine care. For those that had bacteriologically confirmed TB at treatment initiation and can produce sputum without induction, sputum culture will be performed approximately 6 months after the end of treatment to measure disease recurrence. The primary endpoint is a composite unfavourable outcome measured over 12 months from TB treatment initiation defined as either poor end of treatment outcome (lost to follow-up, death, or treatment failure) or treatment recurrence measured 6 months after the scheduled end of treatment. This study will also evaluate the effectiveness, feasibility, and cost-effectiveness of DAT systems for DS-TB patients. DISCUSSION: This trial will evaluate the impact and contextual factors of medication label and smart pillbox with a differentiated response to patient care, among adult pulmonary DS-TB participants in Ethiopia. If successful, this evaluation will generate valuable evidence via a shared evaluation framework for optimal use and scale-up. TRIAL REGISTRATION: Pan African Clinical Trials Registry PACTR202008776694999, https://pactr.samrc.ac.za/TrialDisplay.aspx?TrialID=12241 , registered on August 11, 2020

Considering equity in priority setting using transmission models : Recommendations and data needs

OBJECTIVES: Disease transmission models are used in impact assessment and economic evaluations of infectious disease prevention and treatment strategies, prominently so in the COVID-19 response. These models rarely consider dimensions of equity relating to the differential health burden between individuals and groups. We describe concepts and approaches which are useful when considering equity in the priority setting process, and outline the technical choices concerning model structure, outputs, and data requirements needed to use transmission models in analyses of health equity. METHODS: We reviewed the literature on equity concepts and approaches to their application in economic evaluation and undertook a technical consultation on how equity can be incorporated in priority setting for infectious disease control. The technical consultation brought together health economists with an interest in equity-informative economic evaluation, ethicists specialising in public health, mathematical modellers from various disease backgrounds, and representatives of global health funding and technical assistance organisations, to formulate key areas of consensus and recommendations. RESULTS: We provide a series of recommendations for applying the Reference Case for Economic Evaluation in Global Health to infectious disease interventions, comprising guidance on 1) the specification of equity concepts; 2) choice of evaluation framework; 3) model structure; and 4) data needs. We present available conceptual and analytical choices, for example how correlation between different equity- and disease-relevant strata should be considered dependent on available data, and outline how assumptions and data limitations can be reported transparently by noting key factors for consideration. CONCLUSIONS: Current developments in economic evaluations in global health provide a wide range of methodologies to incorporate equity into economic evaluations. Those employing infectious disease models need to use these frameworks more in priority setting to accurately represent health inequities. We provide guidance on the technical approaches to support this goal and ultimately, to achieve more equitable health policies

Considering equity in priority setting using transmission models: Recommendations and data needs.

OBJECTIVES: Disease transmission models are used in impact assessment and economic evaluations of infectious disease prevention and treatment strategies, prominently so in the COVID-19 response. These models rarely consider dimensions of equity relating to the differential health burden between individuals and groups. We describe concepts and approaches which are useful when considering equity in the priority setting process, and outline the technical choices concerning model structure, outputs, and data requirements needed to use transmission models in analyses of health equity. METHODS: We reviewed the literature on equity concepts and approaches to their application in economic evaluation and undertook a technical consultation on how equity can be incorporated in priority setting for infectious disease control. The technical consultation brought together health economists with an interest in equity-informative economic evaluation, ethicists specialising in public health, mathematical modellers from various disease backgrounds, and representatives of global health funding and technical assistance organisations, to formulate key areas of consensus and recommendations. RESULTS: We provide a series of recommendations for applying the Reference Case for Economic Evaluation in Global Health to infectious disease interventions, comprising guidance on 1) the specification of equity concepts; 2) choice of evaluation framework; 3) model structure; and 4) data needs. We present available conceptual and analytical choices, for example how correlation between different equity- and disease-relevant strata should be considered dependent on available data, and outline how assumptions and data limitations can be reported transparently by noting key factors for consideration. CONCLUSIONS: Current developments in economic evaluations in global health provide a wide range of methodologies to incorporate equity into economic evaluations. Those employing infectious disease models need to use these frameworks more in priority setting to accurately represent health inequities. We provide guidance on the technical approaches to support this goal and ultimately, to achieve more equitable health policies