Interannual Variability of Nitrogen Limitation in a Desert Lake: Influence of Regional Climate

1994 ◽  
Vol 51 (4) ◽  
pp. 862-872 ◽  
Author(s):  
Martin E. Lebo ◽  
John E. Reuter ◽  
Charles R. Goldman ◽  
Cathryn L. Rhodes
Keyword(s):  
Regional Climate ◽  
Nutrient Status ◽  
Weather Data ◽  
Systematic Evaluation ◽  
Nutrient Ratios ◽  
N Availability ◽  
Pyramid Lake ◽  
N Limitation ◽  
Climatic Variations ◽  
Desert Lake

A systematic evaluation of limnological and experimental indicators of nutrient limitation in Pyramid Lake during 1989–92 clearly show that N is the nutrient most limiting to phytoplankton. This conclusion is supported by dissolved inorganic nutrient ratios, seston elemental composition, nutrient enrichment bioassay experiments, and blooms of N2-fixing algae. However, the degree of N limitation expressed during the three years varied considerably. A comparison of interannual patterns of N limitation with weather data collected at the lake suggests that differences among years can be attributed to climatic variations. Our study indicates that climatic variations affect N availability by altering the timing of winter deep mixing, varying the potential for upwelling during spring, and varying the rate of spring warming of surface waters. Summer wind patterns also appear to be an integral factor controlling initiation, development, and collapse of the annual bloom of Nodularia spumigena, a N2-fixing blue-green alga. The results of this study emphasize the need to consider climatic variations in assessing the general nutrient status of lakes.

scholarly journals Development of an Online Tool for Tracking Soil Nitrogen to Improve the Environmental Performance of Maize Production

2021 ◽  
Vol 13 (10) ◽  
pp. 5649
Author(s):  
Giovani Preza-Fontes ◽  
Junming Wang ◽  
Muhammad Umar ◽  
Meilan Qi ◽  
Kamaljit Banger ◽  
...  
Keyword(s):  
Real Time ◽  
N Uptake ◽  
Growing Season ◽  
Weather Data ◽  
N Availability ◽  
Soil N ◽  
N Losses ◽  
Online Tool ◽  
Support Tool ◽  
Soil N Availability

Freshwater nitrogen (N) pollution is a significant sustainability concern in agriculture. In the U.S. Midwest, large precipitation events during winter and spring are a major driver of N losses. Uncertainty about the fate of applied N early in the growing season can prompt farmers to make additional N applications, increasing the risk of environmental N losses. New tools are needed to provide real-time estimates of soil inorganic N status for corn (Zea mays L.) production, especially considering projected increases in precipitation and N losses due to climate change. In this study, we describe the initial stages of developing an online tool for tracking soil N, which included, (i) implementing a network of field trials to monitor changes in soil N concentration during the winter and early growing season, (ii) calibrating and validating a process-based model for soil and crop N cycling, and (iii) developing a user-friendly and publicly available online decision support tool that could potentially assist N fertilizer management. The online tool can estimate real-time soil N availability by simulating corn growth, crop N uptake, soil organic matter mineralization, and N losses from assimilated soil data (from USDA gSSURGO soil database), hourly weather data (from National Weather Service Real-Time Mesoscale Analysis), and user-entered crop management information that is readily available for farmers. The assimilated data have a resolution of 2.5 km. Given limitations in prediction accuracy, however, we acknowledge that further work is needed to improve model performance, which is also critical for enabling adoption by potential users, such as agricultural producers, fertilizer industry, and researchers. We discuss the strengths and limitations of attempting to provide rapid and cost-effective estimates of soil N availability to support in-season N management decisions, specifically related to the need for supplemental N application. If barriers to adoption are overcome to facilitate broader use by farmers, such tools could balance the need for ensuring sufficient soil N supply while decreasing the risk of N losses, and helping increase N use efficiency, reduce pollution, and increase profits.

The importance of nitrogen in Pyramid Lake (Nevada, USA), a saline, desert lake

Hydrobiologia ◽  
1993 ◽  
Vol 267 (1-3) ◽  
pp. 179-189 ◽  
Author(s):  
John E. Reuter ◽  
Cathryn L. Rhodes ◽  
Martin E. Lebo ◽  
Mandy Kotzman ◽  
Charles R. Goldman
Keyword(s):  
Pyramid Lake ◽  
Saline Desert ◽  
Desert Lake

Designing photovoltaic arrays for groundwater pumping for remote agriculture using synthetically generated daily rainfall and irrigation needs

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kurt A. Wurthmann
Keyword(s):  
Peak Power ◽  
Regional Climate ◽  
Daily Rainfall ◽  
South Florida ◽  
Weather Data ◽  
Diesel Generator ◽  
Generator System ◽  
Content Type ◽  
Pv Array ◽  
Crop Irrigation

Purpose This study aims to provide a new method for precisely sizing photovoltaic (PV) arrays for standalone, direct pumping PV Water Pumping (PVWP) systems for irrigation purposes. Design/methodology/approach The method uses historical weather data and considers daily variability in regional temperatures and rainfall, crop evapotranspiration rates and seasonality effects, all within a nonparametric bootstrapping approach to synthetically generate daily rainfall and crop irrigation needs. These needs define the required daily supply of pumped water to achieve a user-specified level of reliability, which provides the input to an intuitive approach for PV array sizing. An economic comparison of the costs for the PVWP versus a comparably powered diesel generator system is provided. Findings Pumping 22.8646 m³/day of water would meet the pasture crop irrigation needs on a one-acre (4046.78 m²) tract of land in South Florida, with 99.9% reliability. Given the specified assumptions, an 8.4834 m² PV array, having a peak power of 1.1877 (kW), could provide the 1.2347 (kWh/day) of hydraulic energy needed to supply this volume over a total head of 20 meters. The PVWP system is the low-cost option when diesel prices are above $0.90/liter and total installed PV array costs are fixed at $2.00/Watt peak power or total installed PV array costs are below $1.50/Watt peak power and diesel prices are fixed at $0.65/liter. Originality/value Because the approach is not dependent on the shapes of the sampling distributions for regional climate factors and can be adapted to consider different types of crops, it is highly portable and applicable for precisely determining array sizes for standalone, direct pumping PVWP systems for irrigating diverse crop types in diverse regions.

Use of hot KCl-NH4-N to estimate fertilizer N requirements

1997 ◽  
Vol 77 (2) ◽  
pp. 161-166 ◽  
Author(s):  
C. A. Campbell ◽  
Y. W. Jamel ◽  
A. Jalil ◽  
J. Schoenau
Keyword(s):  
N Mineralization ◽  
Growth Models ◽  
Growing Season ◽  
Order Rate Constant ◽  
Weather Data ◽  
N Availability ◽  
Fertilizer N ◽  
Available N ◽  
Mineralizable N ◽  
Potentially Mineralizable N

We need an easy-to-use chemical index for estimating the amount of N that becomes available during the growing season, to improve N use efficiency. This paper discusses how producers may, in future, use crop growth models that incorporate indices of soil N availability, to make more accurate, risk-sensitive estimates of fertilizer N requirements. In a previous study, we developed an equation, using 42 diverse Saskatchewan soils, that related potentially mineralizable N (N0) to NH4N extracted with hot 2 M KCl (X), (i.e., N0 = 37.7 + 7.7X, r2 = 0.78). We also established that the first order rate constant (k) for N mineralization at 35°C is indeed a constant for arable prairie soils (k = 0.067 wk−1). We modified the N submodel of CERES-wheat to include k and N0 (values of N0 were derived from the hot KCl test). With long-term weather data (precipitation and temperature) as input, this model was used to estimate probable N mineralization during a growing season and yield of wheat (grown on fallow or stubble), in response to fertilizer N rates at Swift Current. The model output indicated that the amount of N mineralized in a growing season for wheat on fallow was similar to that for wheat on stubble, as we hypothesized. Further the model indicated that rate of fertilizer N had only minimal effect on N mineralized. We concluded that, despite the importance of knowing the Nmin capability of a soil, it is available water, initial levels of available N and rate of fertilizer N that are the main determinants of yield in this semiarid environment. The theoretical approach we have proposed must be validated under field conditions before it can be adopted for use. Key words: N mineralization, Hot KCl-NH4-N, potentially mineralizable N, CERES-wheat model

Cereal yield forecasting combining satellite drought-based indices, regional climate and weather data using machine learning approaches in Morocco

2021 ◽  
Author(s):  
El houssaine Bouras ◽  
Lionel Jarlan ◽  
Salah Er-Raki ◽  
Riad Balaghi ◽  
Abdelhakim Amazirh ◽  
...  
Keyword(s):  
Machine Learning ◽  
Regional Climate ◽  
Model Development ◽  
Machine Learning Algorithms ◽  
Weather Data ◽  
Drought Indices ◽  
Support Vector ◽  
Learning Approaches ◽  
Climate Data ◽  
Yield Forecasting

<p>Cereals are the main crop in Morocco. Its production exhibits a high inter-annual due to uncertain rainfall and recurrent drought periods. Considering the importance of this resource to the country's economy, it is thus important for decision makers to have reliable forecasts of the annual cereal production in order to pre-empt importation needs. In this study, we assessed the joint use of satellite-based drought indices, weather (precipitation and temperature) and climate data (pseudo-oscillation indices including NAO and the leading modes of sea surface temperature -SST- in the mid-latitude and in the tropical area) to predict cereal yields at the level of the agricultural province using machine learning algorithms (Support Vector Machine -SVM-, Random forest -FR- and eXtreme Gradient Boost -XGBoost-) in addition to Multiple Linear Regression (MLR). Also, we evaluate the models for different lead times along the growing season from January (about 5 months before harvest) to March (2 months before harvest). The results show the combination of data from the different sources outperformed the use of a single dataset; the highest accuracy being obtained when the three data sources were all considered in the model development. In addition, the results show that the models can accurately predict yields in January (5 months before harvesting) with an R² = 0.90 and RMSE about 3.4 Qt.ha<sup>-1</sup>.  When comparing the model’s performance, XGBoost represents the best one for predicting yields. Also, considering specific models for each province separately improves the statistical metrics by approximately 10-50% depending on the province with regards to one global model applied to all the provinces. The results of this study pointed out that machine learning is a promising tool for cereal yield forecasting. Also, the proposed methodology can be extended to different crops and different regions for crop yield forecasting.</p>

The importance of nitrogen in Pyramid Lake (Nevada, USA), a saline, desert lake

1993 ◽  
pp. 179-189 ◽  
Author(s):  
John E. Reuter ◽  
Cathryn L. Rhodes ◽  
Martin E. Lebo ◽  
Mandy Kotzman ◽  
Charles R. Goldman
Keyword(s):  
Pyramid Lake ◽  
Saline Desert ◽  
Desert Lake

Nutrients in Salmonid Ecosystems: Sustaining Production and Biodiversity

2003 ◽  
Keyword(s):  
Pacific Northwest ◽  
Nutrient Release ◽  
Nutrient Status ◽  
N Availability ◽  
P Availability ◽  
Streams And Rivers ◽  
Salmon River ◽  
P Limitation ◽  
The Pacific ◽  
Simplifying Assumptions

<em>Abstract.</em>—Recent studies have shown that anadromous fish deliver ecologically significant quantities of marine-derived nitrogen (N), phosphorus (P), and organic carbon (C) to lakes, rivers, and streams of the Pacific Northwest. These marine-derived nutrients (MDN) can influence the ecological functioning of receiving streams through nutrient release and food availability. In Idaho, populations of anadromous salmon have declined dramatically with many formerly salmon-bearing streams now receiving no MDN supplementation. In order to assess how the loss of MDN may influence Idaho streams and rivers, we examined the current nutrient status of streams and rivers in Idaho with particular emphasis on the limiting role of N and P. We also generated a range of estimates of the historic and current affects of MDN on selected basins of the Salmon River, Idaho. Our analysis indicates that 25–50% of Idaho’s streams are potentially nutrient limited. Further analysis suggests that N and P limitation occurred in an approximately equal number of streams. Historic contributions of MDN to the Salmon River had varying potential to influence N and P availability, ranging from undetectable to resulting in a doubling of N availability. The level of influence depended upon location within the basin and the choices made regarding some simplifying assumptions. Finally, we discuss the effectiveness of artificial fertilization as a means of compensating for lost MDN and suggest that a spiraling approach be used to design and monitor fertilization treatments.

scholarly journals Soil microbial nutrient constraints along a tropical forest elevation gradient: a belowground test of a biogeochemical paradigm

2015 ◽  
Vol 12 (20) ◽  
pp. 6071-6083 ◽  
Author(s):  
A. T. Nottingham ◽  
B. L. Turner ◽  
J. Whitaker ◽  
N. J. Ostle ◽  
N. P. McNamara ◽  
...  
Keyword(s):  
Tropical Forests ◽  
Elevation Gradient ◽  
Hydrolytic Enzymes ◽  
Nutrient Status ◽  
N Availability ◽  
P Availability ◽  
Total N ◽  
Peruvian Andes ◽  
Soil Microbial ◽  
Microbial Nutrient Status

Abstract. Aboveground primary productivity is widely considered to be limited by phosphorus (P) availability in lowland tropical forests and by nitrogen (N) availability in montane tropical forests. However, the extent to which this paradigm applies to belowground processes remains unresolved. We measured indices of soil microbial nutrient status in lowland, sub-montane and montane tropical forests along a natural gradient spanning 3400 m in elevation in the Peruvian Andes. With increasing elevation there were marked increases in soil concentrations of total N, total P, and readily exchangeable P, but a decrease in N mineralization determined by in situ resin bags. Microbial carbon (C) and N increased with increasing elevation, but microbial C : N : P ratios were relatively constant, suggesting homeostasis. The activity of hydrolytic enzymes, which are rich in N, decreased with increasing elevation, while the ratio of enzymes involved in the acquisition of N and P increased with increasing elevation, further indicating an increase in the relative demand for N compared to P with increasing elevation. We conclude that soil microorganisms shift investment in nutrient acquisition from P to N between lowland and montane tropical forests, suggesting that different nutrients regulate soil microbial metabolism and the soil carbon balance in these ecosystems.

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