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Monitoring of carbon-water fluxes at Eurasian meteorological stations using random forest and remote sensing
AbstractSimulating the carbon-water fluxes at more widely distributed meteorological stations based on the sparsely and unevenly distributed eddy covariance flux stations is needed to accurately understand the carbon-water cycle of terrestrial ecosystems. We established a new framework consisting of machine learning, determination coefficient (R2), Euclidean distance, and remote sensing (RS), to simulate the daily net ecosystem carbon dioxide exchange (NEE) and water flux (WF) of the Eurasian meteorological stations using a random forest model or/and RS. The daily NEE and WF datasets with RS-based information (NEE-RS and WF-RS) for 3774 and 4427 meteorological stations during 2002–2020 were produced, respectively. And the daily NEE and WF datasets without RS-based information (NEE-WRS and WF-WRS) for 4667 and 6763 meteorological stations during 1983–2018 were generated, respectively. For each meteorological station, the carbon-water fluxes meet accuracy requirements and have quasi-observational properties. These four carbon-water flux datasets have great potential to improve the assessments of the ecosystem carbon-water dynamics.
Wpływ fal upałów i susz, wahań poziomów wody i dostępności nutrientów na fluorescencję chlorofilu (SIF), fotosyntezę, parametry spektralne i biofizyczne roślinności torfowiska na gradiencie zmian poziomu wód i składników pokarmowych
Silicon-induced photosynthetic adaptations in common buckwheat under salt stress revealed by prompt chlorophyll a fluorescence analysis
Abstract This study aimed at investigating the protective role of silicon (Si) in mitigating salt-induced damage in common buckwheat plants (Fagopyrum esculentum cv. Smuga). Twenty one-day-old seedlings were subjected to salt stress by irrigating 50 mM sodium chloride solutions for seven days, with or without Si (two foliar applications with 1 mM sodium metasilicate nonahydrate). Salt stress significantly altered the chlorophyll a fluorescence transient (OJIP) curve, disrupting energy flow and electron transport in photosystem II (PSII), as reflected in the O-J, J-I, and I-P phases, along with the emergence of a positive K-band indicating damage to the oxygen-evolving complex (OEC). Silicon application mitigated these effects, stabilizing the OEC and thylakoid membrane integrity while improving JIP test parameters and reducing excessive energy absorption, dissipation, and unregulated energy loss per reaction center. Silicon-treated plants under salt stress exhibited enhanced photochemical quenching, reduced regulatory energy dissipation, and decreased photosystem I (PSI) over-reduction. A significant increase in open PSI centers was observed, improving the balance and functionality between PSI and photosystem II. The application of Si resulted in significant photosynthetic improvements, which were also paired with enhanced morphological traits, such as increased root length and leaf thickness in saline conditions. Overall, findings indicate that exogenous Si helps to reduce salt-induced stress by enhancing photosynthetic efficiency in plants, positioning it as a promising strategy for improving crop performance in saline environments.
A multi-year study of ecosystem production and its relation to biophysical factors over a temperate peatland
A Multi-Model Gap-Filling Strategy Increases the Accuracy of GPP Estimation from Periodic Chamber-Based Flux Measurements on Sphagnum-Dominated Peatland
Gross primary productivity (GPP), the primary driver of carbon accumulation, governs the sequestration of atmospheric CO2 into biomass. However, GPP cannot be measured directly, as photosynthesis and respiration are simultaneous. At canopy level in plot-scale studies, GPP can be estimated through the closed chamber-based measurements of net ecosystem exchange (NEE) and ecosystem respiration (Reco). This technique is cost-effective and widely used in small-scale studies with short vegetation, but measurements are periodic-based and require temporal interpolations. The rectangular hyperbolic model (RH) was the basis of this study, developing two temperature-dependent factors following a linear and exponential shift in GPP when the temperature oscillates from the optimum for vegetation performance. Additionally, a water table depth (WTD)-dependent model and an exponential model were tested. In the peak season, modified RH models showed the best performance, while for the rest of the year, the best model varied for each subplot. The statistical results demonstrate the limitations of assuming the light-use efficiency as a fixed shape mechanism (using only one model). Therefore, a multi-model approach with the best performance model selected for each period is proposed to improve GPP estimations for peatlands.
Cloud-Based Remote Sensing for Wetland Monitoring—A Review
The rapid expansion of remote sensing provides recent and developed advances in monitoring wetlands. Integrating cloud computing with these techniques has been identified as an effective tool, especially for dealing with heterogeneous datasets. In this study, we conducted a systematic literature review (SLR) to determine the current state-of-the-art knowledge for integrating remote sensing and cloud computing in the monitoring of wetlands. The results of this SLR revealed that platform-as-a-service was the only cloud computing service model implemented in practice for wetland monitoring. Remote sensing applications for wetland monitoring included prediction, time series analysis, mapping, classification, and change detection. Only 51% of the reviewed literature, focused on the regional scale, used satellite data. Additionally, the SLR found that current cloud computing and remote sensing technologies are not integrated enough to benefit from their potential in wetland monitoring. Despite these gaps, the analysis revealed that economic benefits could be achieved by implementing cloud computing and remote sensing for wetland monitoring. To address these gaps and pave the way for further research, we propose integrating cloud computing and remote sensing technologies with the Internet of Things (IoT) to monitor wetlands effectively.
The effect of climate manipulation on CO2 fluxes in a temperate peatland: higher fluxes, more frequent irregularities, and seasonality displacements
Effect of Subirrigation and Silicon Antitranspirant Application on Biomass Yield and Carbon Dioxide Balance of a Three-Cut Meadow
Meadows are valuable areas that play an important role in the carbon cycle. Depending on several factors, these areas can be carbon sinks or net emitters of carbon dioxide (CO2) into the atmosphere. In the present study, the use of an antitranspirant (AT) with silicon and the groundwater level in a subirrigation system in a three-cut meadow were evaluated on the carbon dioxide exchange balance and the yield of aboveground biomass. The study was carried out in four experimental plots: with high groundwater level (HWL), with a high water level with AT application (HWL_Si), with a lower groundwater level (LWL), and with a lower groundwater level and AT application (LWL_Si). Flux measurements were made using the closed dynamic chamber method. In the drier and colder 2021, the meadow was a net CO2 emitter (mean annual net ecosystem exchange (NEE) of all plots: +247.4 gCO2-C·m−2y−1), whereas in the more wet and warmer 2022, assimilation outweighed emissions (mean annual NEE of all plots: −187.4 gCO2-C·m−2y−1). A positive effect of the silicon antitranspirant application was observed on the reduction of carbon dioxide emissions and the increase of gross primary production (GPP) from the plots with higher groundwater levels. For the area with lower water levels, the positive impact of AT occurred only in the second year of the experiment. The yield of aboveground biomass was higher by 5.4% (in 2021) up to 11.7% (in 2022) at the plot with the higher groundwater level. However, the application of AT with silicon contributed to yield reduction in each cut, regardless of the groundwater level. On an annual basis, AT application with silicon reduced the yield by 11.1–17.8%.
Automatyczna samojezdna platforma pomiarowa do pomiarów wymiany gazów szklarniowych pomiędzy podłożem a atmosferą oraz do pomiarów charakterystyk spektralnych powierzchni
High-throughput phenotyping of buckwheat (Fagopyrum esculentum Moench.) genotypes under water stress: exploring drought resistance for sustainable agriculture
Abstract Background As global agriculture faces the challenge of climate change, characterized by longer and more severe drought episodes, there is an increasing need for crop diversification and improved plant breeding. Buckwheat is one of the climate-resilient candidates for future important crops with remarkable adaptability to various biotic and abiotic stresses. As an underbred crop, a large number of genotypes should be assessed for the breeding of superior plants. Therefore, this study investigates the response of various buckwheat genotypes to water stress by high-throughput phenotyping and auxiliary plant physiology measurements. Results We assessed six buckwheat genotypes from different regions under mild and severe water stress, focusing on morphological and physiological changes to understand drought tolerance mechanisms. Our findings revealed that reallocation of assimilated carbon from growth to secondary metabolite production is a common response to drought stress. Among the genotypes tested, Panda emerged as the most drought-resistant, with its morphology remaining the most stable under mild water stress and its ability to rapidly accumulate protective pigments in response to drought. Silver Hull also demonstrated resilience, maintaining its aboveground biomass under mild water stress at levels comparable to the control group. Additionally, the response magnitude to drought stress was linked to the biomass production potential of the genotypes, which was higher for those from warmer regions (Bhutan, Zimbabwe) and lower for those from colder regions (Poland, Canada). Conclusion The diversity in genotypic responses highlights the significant role of genetic variability in shaping drought resistance strategies in buckwheat. This research not only enhances our understanding of buckwheat’s physiological responses to water stress but also holds promise for developing drought-resistant buckwheat varieties. These advancements are crucial for promoting sustainable agriculture in the face of climate change.
Sun-induced fluorescence spectrum as a tool for assessing peatland vegetation productivity in the framework of warming and reduced precipitation experiment
Reakcja fluorescencji indukowanej promieniowaniem słonecznym oraz fotosyntezy roślinności torfowiska na stres wywołany symulowanym deficytem wodnym i podwyższoną temperaturą w warunkach klimatycznego eksperymentu manipulacyjnego
Challenges and Limitations of Remote Sensing Applications in Northern Peatlands: Present and Future Prospects
This systematic literature review (SLR) provides a comprehensive overview of remote sensing (RS) applications in northern peatlands from 2017 to 2022, utilising various platforms, including in situ, UAV, airborne, and satellite technologies. It addresses the challenges and limitations presented by the sophisticated nature of northern peatland ecosystems. This SLR reveals an in-creased focus on mapping, monitoring, and hydrology but identifies noticeable gaps in peatland degradation research. Despite the benefits of remote sensing, such as extensive spatial coverage and consistent monitoring, challenges persist, including high costs, underexplored areas, and limitations in hyperspectral data application. Fusing remote sensing data with on-site research offers new insights for regional peatland studies. However, challenges arise from issues like the cost of high-resolution data, coverage limitations, and inadequate field validation data in remote areas. This review suggests refining methodologies, validating with high-resolution data, and addressing these limitations for future research.
Nonphotochemical quenching does not alter the relationship between sun‐induced fluorescence and gross primary production under heatwave
Photosynthetic Responses of Peat Moss (Sphagnum spp.) and Bog Cranberry (Vaccinium oxycoccos L.) to Spring Warming
The rising global temperature makes understanding the impact of warming on plant physiology in critical ecosystems essential, as changes in plant physiology can either help mitigate or intensify climate change. The northern peatlands belong to the most important parts of the global carbon cycle. Therefore, knowledge of the ongoing and future climate change impacts on peatland vegetation photosynthesis is crucial for further refinement of peatland or global carbon cycle and vegetation models. As peat moss (Sphagnum spp.) and bog cranberry (Vaccinium oxycoccos L.) represent some of the most common plant functional groups of peatland vegetation, we examined the impact of experimental warming on the status of their photosynthetic apparatus during the early vegetation season. We also studied the differences in the winter to early spring transition of peat moss and bog cranberry photosynthetic activity. We have shown that peat moss starts photosynthetic activity earlier because it relies on light-dependent energy dissipation through the winter. However, bog cranberry needs a period of warmer temperature to reach full activity due to the sustained, non-regulated, heat dissipation during winter, as suggested by the doubling of photosystem II efficiency and 36% decrease in sustained heat dissipation between the mid-March and beginning of May. The experimental warming further enhanced the performance of photosystem II, indicated by a significant increase in the photosystem II performance index on an absorption basis due to warming. Therefore, our results suggest that bog cranberry can benefit more from early spring warming, as its activity is sped up more compared to peat moss. This will probably result in faster shrub encroachment of the peatlands in the warmer future. The vegetation and carbon models should take into account the results of this research to predict the peatland functions under changing climate conditions.
Evaluating Remote Sensing Metrics for Land Surface Phenology in Peatlands
Vegetation phenology is an important indicator of climate change and ecosystem productivity. However, the monitoring of vegetation generative phenology through remote sensing techniques does not allow for species-specific retrieval in mixed ecosystems; hence, land surface phenology (LSP) is used instead of traditional plant phenology based on plant organ emergence and development observations. Despite the estimated timing of the LSP parameters being dependent on the vegetation index (VI) used, inadequate attention was paid to the evaluation of the commonly used VIs for LSP of different vegetation covers. We used two years of data from the experimental site in central European peatland, where plots of two peatland vegetation communities are under a climate manipulation experiment. We assessed the accuracy of LSP retrieval by simple remote sensing metrics against LSP derived from gross primary production and canopy chlorophyll content time series. The product of Near-Infrared Reflectance of Vegetation and Photosynthetically Active Radiation (NIRvP) and Green Chromatic Coordinates (GCC) was identified as the best-performing remote sensing metrics for peatland physiological and structural phenology, respectively. Our results suggest that the changes in the physiological phenology due to increased temperature are more prominent than the changes in the structural phenology. This may mean that despite a rather accurate assessment of the structural LSP of peatland by remote sensing, the changes in the functioning of the ecosystem can be underestimated by simple VIs. This ground-based phenological study on peatlands provides the base for more accurate monitoring of interannual variation of carbon sink strength through remote sensing.
Active afforestation of drained peatlands is not a viable option under the EU Nature Restoration Law
AbstractThe EU Nature Restoration Law (NRL) is critical for the restoration of degraded ecosystems and active afforestation of degraded peatlands has been suggested as a restoration measure under the NRL. Here, we discuss the current state of scientific evidence on the climate mitigation effects of peatlands under forestry. Afforestation of drained peatlands without restoring their hydrology does not fully restore ecosystem functions. Evidence on long-term climate benefits is lacking and it is unclear whether CO2 sequestration of forest on drained peatland can offset the carbon loss from the peat over the long-term. While afforestation may offer short-term gains in certain cases, it compromises the sustainability of peatland carbon storage. Thus, active afforestation of drained peatlands is not a viable option for climate mitigation under the EU Nature Restoration Law and might even impede future rewetting/restoration efforts. Instead, restoring hydrological conditions through rewetting is crucial for effective peatland restoration.