Remote Sensing of Sun-Induced Chlorophyll Fluorescence for Advanced Ecosystem Evapotranspiration Estimates

A precise ecosystem evapotranspiration (ET) estimate is essential for understanding the complex relationship between plants' energy-water-carbon fluxes. Besides, robust ecosystem ET estimation under different water stresses can provide insight into plants' response to extreme weather and environmental conditions. However, for such very preciseness, we must accept the individual and comprehensive interlinked mechanistic relationships between ecosystem ET and its controlling variables for determining the response of ecosystem ET towards extreme climate events. Due to recent drought events in the European continent since the 2000s, many geographical hotspots are getting attention to understanding the complicated mechanistic relationship between ecosystem ET and its controlling variables under such extreme water stress conditions. Consequently, precise ecosystem ET estimation of the European continent's water-stressed ecosystems, i.e. agriculture, will give insight into the sustainability of Europe's agricultural production to ensure sufficient food for millions of people in future. The recent heatwaves and drought in 2018 impacted ecosystem ET substantially over the European continent, which may be a big concern for the European ecosystems' future water, energy, and CO2 balance. The research outcomes of the first research article (c.f. Ahmed et al., 2021) showed that the European continent had up to 50% reduced ecosystem ET compared to a 10-year reference period due to a combined heatwave and drought event in 2018. The results also showed extreme surface air temperature (Tsa) and precipitation (P) anomalies. Due to such extreme climatic phenomena, agricultural land, mixed natural vegetation, and the European continent's non-irrigated agricultural areas were mainly affected. In conclusion, the first research article explains the importance of modelling precise ecosystem ET in variable time and space. However, modelling and estimating precise ecosystem ET is still challenging, especially under extreme climates within continuous time and ample variable space. Remote sensing (RS) data based modelling approaches often encounter uncertainties due to complex parameterizations of different variables for ecosystem ET modelling schemes. Further, uncertainties may be introduced by different data types, data quality, multi-sensor systems, and spatio-temporal resolution of satellite images. The growing advancement of using RS based sun-induced chlorophyll fluorescence (SIF) for ecosystem studies has introduced SIF's use case for ecosystem ET estimates. However, previous studies have limitations due to applying specific ET models, only considering energy or water constraints and different strategies to add SIF in such specifically selected models. The second research article (c.f. Ahmed et al., 2023) investigated possible SIF integration in an advanced ecosystem ET modelling scheme. The research considers the mechanistic relationships between SIF and ecosystem ET and their abiotic and biotic drivers. The results concluded the best possible ways of empirically applying SIF for ecosystem ET estimates under water-limited and well-watered conditions under an experimental setup in maize crop fields in northern Italy. The research assesses the absolute and relative sensitivity of several SIF based ecosystem ET estimation strategies for evolving soil water limitation using extensive in-situ and airborne RS data acquired during the water limitation experiment. The study evaluated five strategies to integrate SIF in an ecosystem ET modelling framework based on the Penman Monteith (PM) and the Ball-Berry-Leuning (BBL) models. The results showed that replacing canopy conductance (including canopy resistance and leaf's net CO2 assimilation rate), leaf area index and net radiation with SIF significantly correspond with in-situ reference ecosystem ET (unit based conversion of measured sap flow) under evolving water limitation. Indeed, considering a single SIF as an indirect proxy for ecosystem ET with a one-to-one relationship showed inconsequential outcomes. In conclusion, the research's outcomes give insight into the importance and scientific advantage of applying SIF in a multi-sensors RS data based framework to increase the sensitivity of SIF based ecosystem ET estimates for evolving water limitations. Besides, the results highlighted the uses of SIF for the scientific advancement of ecosystem drought monitoring. Recent studies have proposed the usability of SIF to establish SIF-based drought indices (DIs) using comparatively coarse spatio-temporal resolution RS data. However, the temporal and spatial sensitivity of such newly proposed SIF-based DIs for growing crop water limitation with higher spatio-temporal resolution RS data must be determined. Therefore, the third Ph.D. research article (in review) conducted a temporal and spatial sensitivity analysis of SIF-based DI for gradually increasing soil and crop water limitation for different crop types. Temporal sensitivity analysis of the study showed that SIF based DI is sensitive throughout evolving soil water limitations, and traditional optical index (OI) based DI is only sensitive at extreme soil water limitations. However, both DIs showed their sensitivity towards the highest soil water limitation. Spatial sensitivity analysis reveals that SIF based DI is sensitive towards decreasing plant available water (PAW) zones and continues till the lowest PAW zones, and OI based DI is only sensitive in the lowest PAW zones. Furthermore, like the temporal analysis, from the spatial analysis, it is also visible that both DIs are sensitive towards the lowest PAW. The research concludes that both SIF based and traditional OI based DIs are sensitive to increasing soil and crop water limitation; however, the experimental setup was not sufficient to say that SIF based DI can be more beneficial for monitoring crop water limitation throughout drought events than OI based DI, instead, both DIs can be applied for monitoring evolving soil and crop water limitation within shorter spatio-temporal scales. Besides, SIF based DI can be applicable for predicting early crop water limitation and promoting incentive preparation for drought, but further studies within different ecosystems with different environmental conditions are needed. In contrast, resulting ecosystem ET values and SIF have been examined with their absolute, relative, temporal, and spatial sensitivities under different soil and crop water availability for monitoring and predicting early plants’ water limitation within different spatio-temporal scales in various spaces and times. Combining all three research articles gives a forward consideration towards the sensitivity of SIF for robust forward ecosystem ET modelling and SIF embedded drought monitoring application within an advanced multi-sensors RS data modelling approach

A First Assessment of the 2018 European Drought Impact on Ecosystem Evapotranspiration

The combined heatwave and drought in 2018 notably affected the state and functioning of European ecosystems. The severity and distribution of this extreme event across ecosystem types and its possible implication on ecosystem water fluxes are still poorly understood. This study estimates spatio-temporal changes in evapotranspiration (ET) during the 2018 drought and heatwave and assesses how these changes are distributed in European ecosystems along climatic gradients. We used the ET eight-day composite product from the MODerate Resolution Imaging Spectroradiometer (MODIS) together with meteorological data from the European Centre for Medium-Range Weather Forecasts (ECMWF ERA5). Our results indicate that ecosystem ET was strongly reduced (up to −50% compared to a 10-year reference period) in areas with extreme anomalies in surface air temperature (Tsa) and precipitation (P) in central, northern, eastern, and western Europe. Northern and Eastern Europe had prolonged anomalies of up to seven months with extreme intensities (relative and absolute) of Tsa, P, and ET. Particularly, agricultural areas, mixed natural vegetation, and non-irrigated agricultural areas were the most affected by the increased temperatures in northern Europe. Our results show contrasting drought impacts on ecosystem ET between the North and South of Europe as well as on ecosystem types

A First Assessment of the 2018 European Drought Impact on Ecosystem Evapotranspiration

The combined heatwave and drought in 2018 notably affected the state and functioning of European ecosystems. The severity and distribution of this extreme event across ecosystem types and its possible implication on ecosystem water fluxes are still poorly understood. This study estimates spatio-temporal changes in evapotranspiration (ET) during the 2018 drought and heatwave and assesses how these changes are distributed in European ecosystems along climatic gradients. We used the ET eight-day composite product from the MODerate Resolution Imaging Spectroradiometer (MODIS) together with meteorological data from the European Centre for Medium-Range Weather Forecasts (ECMWF ERA5). Our results indicate that ecosystem ET was strongly reduced (up to −50% compared to a 10-year reference period) in areas with extreme anomalies in surface air temperature (Tsa) and precipitation (P) in central, northern, eastern, and western Europe. Northern and Eastern Europe had prolonged anomalies of up to seven months with extreme intensities (relative and absolute) of Tsa, P, and ET. Particularly, agricultural areas, mixed natural vegetation, and non-irrigated agricultural areas were the most affected by the increased temperatures in northern Europe. Our results show contrasting drought impacts on ecosystem ET between the North and South of Europe as well as on ecosystem types

Empirical insights on the use of sun-induced chlorophyll fluorescence to estimate short-term changes in crop transpiration under controlled water limitation

Knowledge of actual crop transpiration (T) is important for advanced crop management but challenging to obtain due to the large spatial and temporal variation of T. Remote sensing offers various possibilities to assess T dynamics, while particularly sun-induced chlorophyll fluorescence (SIF) has been demonstrated as a sensitive empirical proxy for T. Despite this success, the advancement of the mechanistic understanding of how SIF relates to T dynamics is key for the future development and implementation of robust and reliable SIF-based T products. This study aims to contribute insights by experimentally assessing the sensitivity of several SIF-based T estimation strategies for evolving soil water limitation. We investigated extensive in situ and airborne data acquired during a water limitation experiment in a maize canopy in northern Italy. We evaluated five empirical strategies to integrate SIF in a T modelling framework based on the Penman-Monteith (PM) and the Ball-Berry-Leuning (BBL) concepts. Our results indicate that replacing model parameters sensitive to canopy conductance with SIF results in the best agreement between modelled and measured T under evolving water limitation. Our study contributes expanding existing knowledge with empirical insights on the sensitivity of SIF based T approaches under increasing soil water limitation at short time scales

Effect of discriminate and indiscriminate use of oxytetracycline on residual status in broiler soft tissues

Aim: This study aimed to evaluate the effects of discriminate and indiscriminate use of oxytetracycline on hematological parameters, residual status in soft tissue of broiler and of thermal effect on oxytetracycline residual status. Materials and Methods: Eighteen, day-old male broiler chickens were purchased and were divided into three different groups (control group, discriminate group, and indiscriminate group). The control group received no antibiotics. The discriminate group received oxytetracycline 1 g/L drinking water for 5 consecutive days, and 10 days' withdrawal period was maintained before sacrifice. The indiscriminate group received oxytetracycline 1 g/L drinking water till the sacrificed day. Blood samples were collected before sacrificing for hematological analysis. After sacrificing liver, kidney, spleen, and muscle samples were collected for analysis of oxytetracycline residues in raw soft tissues. Since meat is used to cook by traditional method in Bangladesh before consumption that is why positive meat samples were cooked by traditional cooking method to evaluate the thermal effect on oxytetracycline residual status as well. Thin-layer chromatography (TLC) was done for screening of oxytetracycline residues in soft tissues. Results: Mean differences of total erythrocyte count (million/mm3), hemoglobin estimation (gm%), and packed cell volume (%) estimation were not statistically significant among the groups. TLC analysis of raw samples showed 100% positive results of all samples collected from the indiscriminate group. In contrast, samples collected from the discriminate group were negative for oxytetracycline residues. In the control group, all samples were negative for oxytetracycline residue. There was a significant (p<0.05) relationship of oxytetracycline residues among three different groups for liver, kidney, spleen, and muscle samples. Positive liver and muscle samples from the indiscriminate group were subjected to thermal treatment by traditional cooking method of Bangladesh. Oxytetracycline residues had found in cooked meat, liver, and juice part, suggesting that antibiotic residues disseminated to juice part from flesh part after cooking. Conclusion: Evidence suggests that proper maintenance of withdrawal period would minimize oxytetracycline residues in broiler soft tissues, whereas antibiotics retained in soft tissues of broiler in case of indiscriminate use. Traditional cooking does not change oxytetracycline residual status in edible tissues. Therefore, awareness regarding the proper maintenance of withdrawal period after antibiotic treatment of broiler is one of the best strategies which may positively reduce the risk of antimicrobial drugs residue in meat

A Survey on Knowledge, Attitude, and Practices of Large-Animal Farmers towards Antimicrobial Use, Resistance, and Residues in Mymensingh Division of Bangladesh

The widespread and indiscriminate use of antimicrobials in food animals is a key contributor to antimicrobial resistance and antimicrobial residue, which have become a growing public and animal health concern in developing countries such as Bangladesh. This study was aimed to assess the knowledge, attitude, and practices (KAP) of large-animal farmers towards antimicrobial use (AMU), antimicrobial resistance (AMR), and antimicrobial residue (AR) with their correlation. A cross-sectional survey was conducted with a structured and pretested questionnaire in the Mymensingh division of Bangladesh. A total of 212 large-animal farmers (dairy, beef fattening, buffalo, sheep, and goat farmers) were surveyed. Results showed that most of the farmers are male (85.8%) and belong to the 18–30 age group (37.3%). About 20.3% had no formal education, and nearly half of the participants (48.1%) received training regarding antibiotic use and resistance. Penicillin is the most common class of antibiotic used (61.8%) in the study area, followed by other antimicrobials. Only 37.7% of the farmers used antimicrobials on the recommendation of their veterinarian. Overall, 41.5%, 42.5%, and 21.7% of farmers possess adequate knowledge and a satisfactory attitude and perform desirable practices, respectively. Farmers in the 31–40 age group have adequate knowledge, attitude, and ability to implement desired practices compared to farmers in the 18–30 age group. Farmers having a graduate or post-graduate degree scored better in relation to knowledge, attitude, and practice than other farmers. Analysis revealed that farmers who received training on AMU and AMR had 10.014 times (OR = 10.014, 95% CIs: 5.252–19.094), 9.409 times (OR = 9.409, 95% CIs: 4.972–17.806), and 25.994 times (OR = 25.994, 95% CIs: 7.73–87.414) better knowledge, attitude, and performance, respectively, compared to their counterparts. A significant proportion of farmers (97.2%) dispose of leftover antibiotics inappropriately. The findings of the present study will be used to intervene in the education and training of the farmers, which will help to limit the indiscriminate and irrational use of antimicrobials, leading to reducing the chances of developing AMR