Constructed wetlands built for water treatment often need biomass harvesting to remove nutrients from the system. Usually harvesting is done during the peak growing season to maximize the amount of ...nutrients removed from the system. This, however, can create huge methane fluxes that escape from plant tissues to the atmosphere. We used manual chambers and eddy covariance measurements to analyze the increase in methane emissions due to the harvesting of two common wetland species, Typha spp. and Schoenoplectus spp., in two climatically different constructed wetlands in Estonia and California. In addition, we determined the biomass nutrient and carbon concentrations from harvested biomass. We found that harvesting during the summer season, e.g. June and August, resulted in a significant release of methane at both sites. At the California site, baseline median methane emissions were 217.6 nmol m−2 s−1, and harvesting resulted in increases to 395.4 nmol m−2 s−1 that decreased to baseline emission within three days. Footprint modeling demonstrated that the emission increases measured by eddy covariance were dominated by contributions from the cut area to the total footprint signal. At the Estonian site, harvesting resulted in methane increases of 15.9 nmol m−2 s−1 to 110.4 nmol m−2 s−1 in August. However, in September and October the emission was significantly lower. Plant biomass analyses showed clear temporal dynamics in terms of nutrient concentration, being highest in summer and lowest in winter. Our experiments indicate that the optimal time for aboveground biomass harvesting is at the end of the growing season before nutrient translocation to belowground plant structures begins coinciding with lowest methane emissions. Therefore, strategic planning of the harvest timing may help reduce greenhouse gas emissions from managed wetlands and thus improve their multi-faceted ecological benefit.
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•Biomass harvesting from constructed wetlands will stimulate methane emissions.•Autumn biomass harvesting has low methane emissions and high nutrient concentration.•Biomass harvesting in autumn allows low methane emissions and retain plant nutrients.•Both chamber and eddy covariance measurements had similar methane emission pattern.
Wetlands and flooded peatlands can sequester large amounts of carbon (C) and have high greenhouse gas mitigation potential. There is growing interest in financing wetland restoration using C markets; ...however, this requires careful accounting of both CO2 and CH4 exchange at the ecosystem scale. Here we present a new model, the PEPRMT model (Peatland Ecosystem Photosynthesis Respiration and Methane Transport), which consists of a hierarchy of biogeochemical models designed to estimate CO2 and CH4 exchange in restored managed wetlands. Empirical models using temperature and/or photosynthesis to predict respiration and CH4 production were contrasted with a more process‐based model that simulated substrate‐limited respiration and CH4 production using multiple carbon pools. Models were parameterized by using a model‐data fusion approach with multiple years of eddy covariance data collected in a recently restored wetland and a mature restored wetland. A third recently restored wetland site was used for model validation. During model validation, the process‐based model explained 70% of the variance in net ecosystem exchange of CO2 (NEE) and 50% of the variance in CH4 exchange. Not accounting for high respiration following restoration led to empirical models overestimating annual NEE by 33–51%. By employing a model‐data fusion approach we provide rigorous estimates of uncertainty in model predictions, accounting for uncertainty in data, model parameters, and model structure. The PEPRMT model is a valuable tool for understanding carbon cycling in restored wetlands and for application in carbon market‐funded wetland restoration, thereby advancing opportunity to counteract the vast degradation of wetlands and flooded peatlands.
Key Points
Using model‐data fusion, we parameterized a hierarchy of biogeochemical models used to estimate CO2 and CH4 exchange in restored wetlands
In a validation exercise, the PEPRMT model was able to explain 70% and 50% of the variance in net exchange of CO2 and CH4, respectively
Simulation of soil carbon availability was critical for accurately predicting CO2 exchange in recently restored wetlands
The complexity and heterogeneity of human water use over large spatial areas and decadal timescales can impede the understanding of hydrological change, particularly in regions with sparse monitoring ...of the water cycle. In the Arkavathy watershed in southern India, surface water inflows to major reservoirs decreased over a 40-year period during which urbanization, groundwater depletion, modification of the river network, and changes in agricultural practices also occurred. These multiple, interacting drivers combined with limited hydrological monitoring make attribution of the causes of diminishing water resources in the watershed challenging and impede effective policy responses. To mitigate these challenges, we developed a novel, spatially distributed dataset to understand hydrological change by characterizing the residual trends in surface water extent that remain after controlling for precipitation variations and comparing the trends with historical land use maps to assess human drivers of change. Using an automated classification approach with subpixel unmixing, we classified water extent in nearly 1700 man-made lakes, or tanks, in Landsat images from 1973 to 2010. The classification results compared well with a reference dataset of water extent of tanks (R2 = 0.95). We modeled the water extent of 42 clusters of tanks in a multiple regression on simple hydrological covariates (including precipitation) and time. Inter-annual variability in precipitation accounted for 63 % of the predicted variability in water extent. However, precipitation did not exhibit statistically significant trends in any part of the watershed. After controlling for precipitation variability, we found statistically significant temporal trends in water extent, both positive and negative, in 13 of the clusters. Based on a water balance argument, we inferred that these trends likely reflect a non-stationary relationship between precipitation and watershed runoff. Independently of precipitation, water extent increased in a region downstream of Bangalore, likely due to increased urban effluents, and declined in the northern portion of the Arkavathy. Comparison of the drying trends with land use indicated that they were most strongly associated with irrigated agriculture, sourced almost exclusively by groundwater. This suggests that groundwater abstraction was a major driver of hydrological change in this watershed. Disaggregating the watershed-scale hydrological response via remote sensing of surface water bodies over multiple decades yielded a spatially resolved characterization of hydrological change in an otherwise poorly monitored watershed. This approach presents an opportunity to understand hydrological change in heavily managed watersheds where surface water bodies integrate upstream runoff and can be delineated using satellite imagery.
Ust-Tsilma Gorka Dronova, T. I.
Anthropology & archeology of Eurasia,
04/2012, Letnik:
50, Številka:
4
Journal Article
Recenzirano
The Gorka circle dance festival, widely known in central Russia in the past, has survived among the priestless Old-Believers of the Ust-Tsilma region in the Republic of Komi. The dance includes seven ...obligatory figures, with a "gorka" song corresponding to each formation. These figures reflect conceptions of the Ust-Tsilma people about the world, and their arrangement on the circle is connected to ideas of eternal motion and rejuvenation of life. During such merrymaking, acquaintances between young men and women occurred, leading to romantic and marriage relationships. The circle dance rites also ensured successful harvests and its preservation honors ancestral values. The article, based on field, research and ethnographic film data, analyzes ways the celebration developed during the twentieth-twenty-first centuries and its significance for Ust-Tsilma's old-believers today.
The aim of the study was to investigate comparative contractility of isolated radial artery segments (n = 50). Phosphodiesterase inhibitor (papaverine) was used in 15 segments; dihydropyridine ...calcium channel antagonist (adalat) was used in 12 segments; calmodulin inhibitor (aminazine) was used in 13 segments; and "nitromixture" (5 mg verapamil hydrochloride, 2.5 mg nitroglycerine, 500-UN heparin, and 300 mL isosmotic Krebs solution) was used in 10 segments. Effect of hyposmotic solution for the morphometric properties of radial artery was analyzed in 22 arterial segments. The data didn't show statistical differences between drugs: "nitromixture" decreased tone by 100 ± 2% (n = 10), papaverine by 100 ± 11% (n = 15), adalat by 95 ± 6.1% (n = 12) and aminazine by 92 ± 11.3% (n = 13) (p > 0.05). The most effective drug in duration was adalat (n = 12, 90 ± 6.5 minutes) versus "nitromixture" (n = 10, 60 ± 9.3 minutes), papaverine (n = 15, 60 ± 4.3 minutes) and aminazine (n = 13, 50 ± 3.2 minutes) (p < 0.05).
In systems with strong seasonal difference in vegetation structure and appearance, multi-temporal imagery can be particularly useful for community- and species-level discrimination. And, since the ...availability of past data for one source of time series images may be limited, so we need to develop multi-temporal and multi-source method for wetland ecosystem monitoring. To perform this type of analysis, the image spectral characteristics comparison between different aquatic macrophytes and different sensors should be studied firstly. We used TM images, Beijing-1 images and HJ-1 images for this analysis and based on the determination of aquatic plant functional types (PFTs). The objectives of this study were: (1) single-sensor single-date aquatic PFT analysis; (2) multi-source single-date diagnostic spectral characteristics analysis and comparison for different aquatic PFTs; (3) multi-source multitemporal diagnostic spectral characteristics analysis for different aquatic PFTs. From this analysis we found that: (1) For the single-date TM data, the diagnostic spectral band and indexes are Band 2, 4, 5, NDVI, and MNDWI; the best temporal for discriminating different Nonpersistent Emergent Wetland PFTs are in low water level periods, and water infilling and subsiding periods for seasonal submerged and floating aquatic macrophyte. Multi-spectral Decision Tree classification method lead the more good results for most of PFTs; (2) the same type of aquatic PFTs have similar and comparable reflectance characteristics between multi-sensor optical data which could satisfy the time series analysis by compensating more available past images; (3) phenological curves and relative canopy moisture curves extracted from time series remote sensing images provide important information for distinguish different PFTs.
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