Long-Term Biosolids Application on Land: Beneficial Recycling of Nutrients or Eutrophication of Agroecosystems?

The impact of repeated application of alkaline biosolids (sewage sludge) products over more than a decade on soil concentrations of nutrients and trace metals, and potential for uptake of these elements by crops was investigated by analyzing soils from farm fields near Oklahoma City. Total, extractable (by the Modified Morgan test), and water-soluble elements, including macronutrients and trace metals, were measured in biosolids-amended soils and, for comparison, in soils that had received little or no biosolids. Soil testing showed that the biosolids-amended soils had higher pH and contained greater concentrations of organic carbon, N, S, P, and Ca than the control soils. Soil extractable P concentrations in the biosolids-amended soils averaged at least 10 times the recommended upper limit for agricultural soils, with P in the amended soils more labile and soluble than the P in control soils. Several trace elements (most notably Zn, Cu, and Mo) had higher total and extractable concentrations in the amended soils compared to the controls. A radish plant assay revealed greater phytoavailability of Zn, P, Mo, and S (but not Cu) in the amended soils. The excess extractable and soluble P in these biosolids-amended soils has created a long-term source of slow-release P that may contribute to the eutrophication of adjacent surface waters and contamination of groundwater. While the beneficial effects of increased soil organic carbon on measures of “soil health” have been emphasized in past studies of long-term biosolids application, the present study reveals that these benefits may be offset by negative impacts on soils, crops, and the environment from excessive nutrient loading.

Evaluating the sensitivity of the LUCI model to GIS datasets to enable robust farm management decisions in New Zealand

<p>Degradation of water quality is a major issue in New Zealand, to which the loss of nitrogen, phosphorus and sediment from agriculture into waterways contributes significantly. To predict and manage diffuse pollution from intensive agriculture it is vital that models are able to spatially map the sources, flows and sinks of nutrients in the landscape and spatially target mitigations. This study investigates the application of one such model, the Land Utilisation Capability Indicator (LUCI). Used in conjunction with OVERSEER, LUCI is a powerful tool to support farm scale land management decision-making. LUCI includes soil, topography and landcover datasets in its analysis. This thesis examines how the quality and resolution of each dataset affects LUCI’s output. Six different case studies are examined, across a range of New Zealand farming systems. This is the most comprehensive study, to date, of LUCI’s sensitivity to input datasets. The results suggest that LUCI nutrient loading estimates are primarily sensitive to soil order, and therefore to changes in order classifications. Utilising different soil datasets in the LUCI model resulted in varying nutrient load predictions. This sensitivity is primarily attributed to the differing hydraulic and phosphorus retention capabilities of the respective soil orders. To test the sensitivity of LUCI to digital elevation model (DEM) resolution, multiple DEMs with varying spatial and vertical resolution were tested. These results strongly indicate that particularly fine resolution DEMs are required to accurately model flat landscapes. It was recognised that LUCI was not using all of the relevant data available in Landcare Research’s S-Map database. LUCI was modified to use more of this information, and alternative methods of incorporating sibling level data in both LUCI and OVERSEER were investigated. Finally, avenues for future development are suggested. Overall, this thesis highlights the potential LUCI has to play a key role in farm scale environmental management.</p>

Evaluating the sensitivity of the LUCI model to GIS datasets to enable robust farm management decisions in New Zealand

<p>Degradation of water quality is a major issue in New Zealand, to which the loss of nitrogen, phosphorus and sediment from agriculture into waterways contributes significantly. To predict and manage diffuse pollution from intensive agriculture it is vital that models are able to spatially map the sources, flows and sinks of nutrients in the landscape and spatially target mitigations. This study investigates the application of one such model, the Land Utilisation Capability Indicator (LUCI). Used in conjunction with OVERSEER, LUCI is a powerful tool to support farm scale land management decision-making. LUCI includes soil, topography and landcover datasets in its analysis. This thesis examines how the quality and resolution of each dataset affects LUCI’s output. Six different case studies are examined, across a range of New Zealand farming systems. This is the most comprehensive study, to date, of LUCI’s sensitivity to input datasets. The results suggest that LUCI nutrient loading estimates are primarily sensitive to soil order, and therefore to changes in order classifications. Utilising different soil datasets in the LUCI model resulted in varying nutrient load predictions. This sensitivity is primarily attributed to the differing hydraulic and phosphorus retention capabilities of the respective soil orders. To test the sensitivity of LUCI to digital elevation model (DEM) resolution, multiple DEMs with varying spatial and vertical resolution were tested. These results strongly indicate that particularly fine resolution DEMs are required to accurately model flat landscapes. It was recognised that LUCI was not using all of the relevant data available in Landcare Research’s S-Map database. LUCI was modified to use more of this information, and alternative methods of incorporating sibling level data in both LUCI and OVERSEER were investigated. Finally, avenues for future development are suggested. Overall, this thesis highlights the potential LUCI has to play a key role in farm scale environmental management.</p>

Phytoplankton Morpho-Functional Trait Variability along Coastal Environmental Gradients

We utilized the trait-based approach in a novel way to examine how specific phytoplankton traits are related to physical features connected to global change, water quality features connected to catchment change, and nutrient availability connected to nutrient loading. For the analyses, we used summertime monitoring data originating from the coastal northern Baltic Sea and generalized additive mixed modeling (GAMM). Of the physical features connected to global climate change, temperature was the most important affecting several studied traits. Nitrogen-fixing, buoyant, non-motile, and autotrophic phytoplankton, as well as harmful cyanobacteria, benefited from a higher temperature. Salinity and stratification did not have clear effects on the traits. Water transparency, which in the Baltic Sea is connected to catchment change, had a mostly negative relation to the studied traits. Harmfulness was negatively correlated with transparency, while the share of non-harmful and large-sized phytoplankton was positively related to it. We used nutrient loading source type and total phosphorus (TP) as proxies for nutrient availability connected to anthropogenic eutrophication. The nutrient loading source type did not relate to any of the traits. Our result showing that N-fixing was not related to TP is discussed. The regionality analysis demonstrated that traits should be calculated in both absolute terms (biomass) and proportions (share of total biomass) to get a better view of community changes and to potentially supplement the environmental status assessments.

Evaluation of nitrogen loading in the last 80 years in an urbanized Asian coastal catchment through the reconstruction of severe contamination period

Most semi-enclosed seas have experienced severe eutrophication owing to high nutrient loading from rivers during rapid population growth periods. In Japan, the coastal areas of some megacities (e.g., Tokyo and Osaka) experienced considerable economic growth during the 1960s–1970s. Therefore, determining the amount of nutrient loading during this period is essential to undertake measures for the conservation of coastal environments. However, determining the nutrient loading that occurred several decades ago is generally difficult owing to lacking water quality records. In this study, the nitrogen loading in the Yamato River catchment, an urbanized coastal catchment in Asia, for 80 years from the 1940s to the 2010s is reconstructed using the Soil and Water Assessment Tool. We considered factors such as population growth, wastewater treatment plant (WWTP) construction, and changes in land and fertilizer usage in different urbanization stages. Results show that the total nitrogen loading in the catchment peaked in the 1970s at 6616 tons/year owing to untreated wastewater discharge and rapid increase in population growth. By reducing 57% of the nitrogen loading in the 2010s from the catchment, WWTPs have been instrumental in improving the water environment. The decrease in and integration of agricultural land has reduced nitrogen loading attributed to nonpoint sources; however, this reduction was not obvious because of the high fertilizer usage before the 2000s. Overall, the findings of this study provide a comprehensive understanding of the impact of rapid urbanization in an Asian coastal catchment on nitrogen loading during the high economic growth period in the past. This study will be useful for the long-term assessment of nutrient loading in other.

Growth and Nitrogen Retranslocation of Nutrient-Loaded Clonal Betula alnoides Transplanted with or without Fertilization

Nutrient loading can improve the growth and nutrient content of nursery-grown Betula alnoides Buch.-Ham. ex D. Don, but it is unknown whether nutrient loading enhances growth and nutrient uptake after transplanting. Plants were grown with three nutrient loading treatments (N100, N200, and N400; 100, 200, and 400 mg N per plant as 15N-urea) in nursery containers and then transplanted into plastic pots, with or without controlled-release fertilizer (F0 and F10, 0 and 10 g per plant). The N400 plants had a smaller size but higher nitrogen concentration relative to the N100 and N200 plants before transplanting. However, 180 days after transplanting, the N200 and N400 plants had superior root collar diameter, root length, and root area compared to the N100 plants, due to an increase in 15N retranslocation to new stems and new leaves. Moreover, transplant fertilization (F10) enhanced the height, root collar diameter, root length, and plant dry mass, but not nitrogen concentration or retranslocation, relative to F0. We recommend that medium- and high-dose nutrient loading is implemented in B. alnoides nurseries to optimize growth after transplanting. Additional fertilizer at transplanting may be advantageous in supporting growth, owing to the rapid depletion of nutrient reserves after planting out in the field.

MAPPING COLOURED DISSOLVED ORGANIC MATTER IN MANILA BAY USING SENTINEL-3 AND WASI

Manila Bay is one of the most significant bodies of water in the Philippines; it has abundant natural resources that have been the source of livelihood and center of socio-economic development for centuries. However, Manila Bay is affected by multiple environmental problems and challenges. These include increased organic and nutrient loading from untreated domestic, industrial, and agricultural wastes and deterioration of marine habitats threatened by anthropogenic activities. Regular water quality monitoring is ideal in these situations, however, sampling by traditional field methods would not be enough to assess the spatial and temporal variation of water quality in Manila Bay. Gathering field data for the whole bay can also be very challenging due to its extent and logistic constraints. Remote sensing fills the need for a frequent full view of Manila Bay’s water quality. This study makes use of existing bio-optical models to estimate colored dissolved organic matter (CDOM) in Manila Bay. CDOM is the mixture of organic molecules from decayed higher plants, algae, and bacteria, and is the colored portion of the total dissolved organic matter. Sentinel-3 images with concurrent field sampling on 19 July 2021 was used to calibrate and validate the bio-optical models implemented in WASI. The parameterization output showed an R2 = 0.579 and RMSE of 1.274 m−1 from lab-measured CDOM fluorescence converted to absorption. The same parameter set was used on a different image with a concurrent water quality survey on 19 May 2021 and resulted to an R2 of 0.72 with the spectrofluorometer yellow substance concentrations.

Spatiotemporal Heterogeneities and Driving Factors of Water Quality and Trophic State of a Typical Urban Shallow Lake (Taihu, China)

Water quality deterioration and eutrophication of urban shallow lakes are global ecological problems with increasing concern and greater environmental efforts. In this study, spatiotemporal changes of water quality and eutrophication over 2015-2019 in Lake Taihu, were assessed using the monthly time series of 7 water quality parameters measured at 17 sites. The whole lake was divided into 7 sub-lakes and trophic condition was evaluated by trophic level index (TLI). Taihu had poor water quality overall which was mainly astricted by the total nitrogen (TN) and the total phosphorus (TP) and maintained a light-eutropher state, but it had improved in the last five years. It is found that all nutrient parameters reached relatively higher concentrations in the northwestern and northern Taihu with combined cluster analysis and spatial interpolation methods. Meiliang Bay was the most polluted and nutrient-rich area. Mann-Kendall test highlighted the fact that the TP and chlorophyll-a (Chl-a) concentrations increased significantly while the TN and five-day biochemical oxygen demand (BOD5) decreased. The nutrient loading input from the northwestern areas with high human activity and the geomorphological characteristic of the northern closed bays were the main contributors to the spatial heterogeneity in water quality. The main driving force of N pollution was the declining river inflow N loading. And P pollution was affected more by accumulated endogenous pollution, decline aquatic plants area, as well as closely linked with algae biomass. Further water pollution and eutrophication mitigation of Taihu should focus on the limitation of algae and those heavily polluted closed bays.