The role of bioirrigation in sediment phosphorus dynamics and blooms of toxic cyanobacteria in a temperate lagoon

A 3-D coupled hydrodynamic-biogeochemical/ecological model was developed and validated for the coastal Gippsland Lakes system, Australia, to explore the importance of bioirrigation on sediment phosphorus dynamics and the subsequent effects on the formation of summer blooms of Nodularia spumigena. Bottom water phosphorus concentrations and sediment phosphorus fluxes were most accurately simulated with bioirrigation implemented into the model. Further model simulations showed that bioirrigation selectively increased the flux of phosphorus relative to nitrogen leading to sediment N:P release ratios as low as 2. High summer phosphorus levels controlled the duration, size and severity of N. spumigena blooms; however, temperature and salinity were the primary factors that determined bloom formation and location. An assessment of sensitivity to model complexity identified that the model could only reproduce the observed N. spumigena bloom size when bioirrigation was implemented, highlighting the ecological importance of bioirrigation in phosphorus cycling and cyanobacteria bloom dynamics.     

Modelling nutrient transport in Currency Creek,NSW with AnnAGNPS and PEST

The modelling package Annualized Agricultural Nonpoint Source Model (AnnAGNPS) was applied to the prediction of export of nitrogen and phosphorus from Currency Creek, a small experimental catchment within the Hawkesbury–Nepean drainage basin of the Sydney Region. The catchment is 255 ha in area and has experienced extensive soil erosion and losses of nutrients from intensive vegetable cultivation, irrigated dairy pasture and poultry farms. Simulations of nitrogen and phosphorus loads in the Currency Creek catchment were performed at various temporal scales and the degree of calibration was quantified by comparing the simulated data with the monitoring results. In addition, the model independent, nonlinear parameter estimation code PEST, was applied for sensitivity testing to determine and assess the relative importance of the key parameters of the model. Event flows were simulated satisfactorily with AnnAGNPS but only moderate accuracy was achieved for prediction of event-based nitrogen and phosphorus exports. The biggest deviations from the measured data were observed for daily simulations but trends in the generated nutrients matched observed data. Despite achieving good resemblance between measured and predicted phosphorus loads the model showed high level of sensitivity to assigned pH values for topsoil. Increase in pH by one unit resulted in up to 34% increase in model generated particulate phosphorus load.     

Bayesian modelling of algal mass occurrences—using adaptive MCMC methods with a lake water quality model

Our study aims to estimate confounded effects of nutrients and grazing zooplankton (Crustacea) on phytoplankton groups—specifically on nitrogen-fixing Cyanobacteria—in the shallow, mesotrophic Lake Pyhäjärvi in the northern hemisphere (Finland, northern Europe, lat. 60°54′–61°06′, long. 22°09′–22°22′). Phytoplankton is modelled with a non-linear dynamic model which describes the succession of three dominant algae groups (Diatomophyceae, Chrysophyceae, nitrogen-fixing Cyanobacteria) and minor groups summed together as a function of total phosphorus, total nitrogen, temperature, global irradiance and crustacean zooplankton grazing. The model is fitted using 8 years of in situ observations and adaptive Markov chain Monte Carlo (MCMC) methods for estimation of model parameters. The approach offers a way to deal with noisy data and a large number of weakly identifiable parameters in a model. From our posterior simulations we calculate the lower limit for zooplankton carbon mass concentration (45 μgC L⁻¹) and the upper limit for total phosphorus concentration (16 μg L⁻¹) that satisfy with 0.95 probability our predefined water quality criteria (Cyanobacteria concentration during late summer period does not exceed the value 0.86 mg L⁻¹). Within the observational range total phosphorus has marginal effect on Cyanobacteria compared to the zooplankton grazing effect, which is temperature-dependent. Extensive fishing efforts are needed to attain the criteria.     

Nutrient monitoring,simulation and management within a major lowland UK river system: the Kennet

This paper describes an assessment of the nitrogen and phosphorus dynamics of the River Kennet in the south east of England. The Kennet catchment (1200 km²) is a predominantly groundwater fed river impacted by agricultural and sewage sources of nutrient (nitrogen and phosphorus) pollution. The results from a suite of simulation models are integrated to assess the key spatial and temporal variations in the nitrogen (N) and phosphorus (P) chemistry, and the influence of changes in phosphorous inputs from a Sewage Treatment Works on the macrophyte and epiphyte growth patterns. The models used are the Export Co-efficient model, the Integrated Nitrogen in Catchments model, and a new model of in-stream phosphorus and macrophyte dynamics: the ‘Kennet’ model. The paper concludes with a discussion on the present state of knowledge regarding the water quality functioning, future research needs regarding environmental modelling and the use of models as management tools for large, nutrient impacted riverine systems.     

Analysis and numerical simulation of phytoplankton–nutrient systems with nutrient loss

The dynamics of a mathematical model of a layer of single phytoplankton species growing over a pool of nutrients, proposed by [A.H. Taylor, J.R.W. Harris, J. Aiken, The interaction of physical and biological process in a model of the vertical distribution of phytoplankton under stratification, Mar. Int. Ecohyrd., J.C. Nihoul (Ed.) 42 (1986) 313–330] is analyzed. Both cases of presence and absence of a phytoplankton in the water below the layer of interest are considered. Positive and elementary stable nonstandard (PESN) methods, having the same qualitative features as the corresponding continuous models, are formulated and analyzed. Biological implications and a set of numerical simulations supporting the mathematical and numerical analysis are also presented.     

Dry season mapping of savanna forage quality, using the hyperspectral Carnegie Airborne Observatory sensor

Forage quality within an African savanna depends upon limiting nutrients (nitrogen and phosphorus) and nutrients that constrain the intake rates (non-digestible fibre) of herbivores. These forage quality nutrients are particularly crucial in the dry season when concentrations of limiting nutrients decline and non-digestible fibres increase. Using artificial neural networks we test the ability of a new imaging spectrometer (CAO Alpha sensor), both alone and in combination with ancillary data, to map quantities of grass forage nutrients in the early dry season within an African savanna. Respectively 65%, 57% and 41%, of the variance in fibre, phosphorus and nitrogen concentrations were explained. We found that all grass forage nutrients show response to fire and soil. Principal component analysis, not only reduced image dimensionality, but was a useful method for removing cross-track illumination effects in the CAO imagery. To further improve the mapping of forage nutrients in the dry season we suggest that spectra within the shortwave infrared (SWIR) region, or additional relevant ancillary data, are required.     

Three-dimensional oligotrophic ecosystem models driven by physical forcing: the Mediterranean Sea case

An analysis of existing biochemical datasets, collected using different measurements methods, confirms peculiarities of the Mediterranean Sea, such as its oligotrophy, easterly decreasing gradients, and influence of hydrodynamics on the biochemical patterns. Thus assessment of this marine environment requires a model based on a three-dimensional characterization of the ecosystem dynamics. The model, which covers all the Mediterranean basin, conceptually takes into accounts the cycles of nitrogen and phosphorus through the detritus and food chains. It includes as major compartments dissolved inorganic nutrients, two pools of phytoplankton producers, one of zooplankton, and detritus. Dynamic of dissolved oxygen is also simulated. Simulations are presented and results from this conceptualization are reported.     

An organic matter and nitrogen dynamics model for the ecological analysis of integrated aquaculture/agriculture systems: II. Model evaluation and application

The performance of a model developed to simulate organic matter and nitrogen dynamics in integrated aquaculture/agriculture systems was evaluated using sensitivity analysis and model verification procedures with data from three sites. The model sensitivity analysis results were used to identify parameters that required high accuracy in measurement, and to suggest areas of future research in integrated aquaculture/agriculture systems. Model sensitivity analysis results showed that research on stocking density, sediment processes and water management practices was required, in order to improve the overall understanding of the functioning of the integrated aquaculture/agriculture system. Results from model verification runs showed that the model performance was satisfactory with respect to fish growth, crop growth, pond and terrestrial nitrogen and organic matter simulations. However, the modeling of phytoplankton biomass was less satisfactory and the results suggested the need for more site-specific calibration of exogenous factors and the consideration of phytoplankton species composition in simulating grazing preferences by fish. Application of the model to investigate the effects of different cycling pathways on nitrogen retention and productivity showed that the recycling of plant wastes to aquaculture ponds had a major effect in reducing system nitrogen losses and increasing system productivity. Sediment organic matter processes were identified as the major determinants of system nitrogen retention, as measured by the nitrogen retention index. The modeling study also showed that the number of linkages between the aquaculture and agriculture components was not directly related to nitrogen retention and productivity in the system. The results of the modeling study suggest that the system nitrogen status may be more important than the number of pathways in determining the number and type of cycling pathways that should be incorporated in integrated aquaculture/agriculture system.     

A simulation model of hydrology and nutrient dynamics in wetlands

A simulation model of the hydrology and nutrient dynamics in wetlands typical of central and north Florida was developed to predict parameters of water depth, recharge, and surface outflow as well as concentrations of total phosphorus, and three nitrogen species. The hydrological portion of the model predicts hydroperiod and depth of inundation for any elevation, and can be used to establish characteristic hydroperiod for vegetation and associations of species. The nutrient portion of the model can be used to predict water quality within, and quality of surface water outflow from natural wetlands, constructed wetlands, and wetlands receiving treated effluent or storm drainage. Programmed in BASIC for simulation on desktop microcomputers, the model is interactive requiring data input such as wetland type, discharge rate, and the concentrations of nutrients in surface water inflow.     

An economic–ecological model to evaluate impacts of nutrient abatement in the Baltic Sea

This paper presents a coupled economic–ecological model that integrates a catchment model with a marine model and incorporates economic data to analyse the long-term economic and ecological consequences of nutrient abatement in the Baltic Sea. The spatially explicit model describes dynamics of soil phosphorus in arable land, developments of nutrient concentrations and phytoplankton biomass in the sea basins, and inter-annual variation in nutrient loads and biophysical processes. The performance of the model is demonstrated by computing the least-cost solution to reach the good environmental state of the sea – as implied by the Baltic Sea Action Plan – within a time span of 40 years. The total cost of achieving this target is 1487 M€ annually. Spatially optimal allocation of load reductions differs from the load reduction targets of the Baltic Sea Action Plan, and focuses more on the control of phosphorus loads.     

An absorption model to determine phytoplankton size classes from satellite ocean colour

We have developed a model linking phytoplankton absorption to phytoplankton size classes (PSCs) that uses a single variable, the optical absorption by phytoplankton at 443 nm, a_ph(443), which can be derived from the inversion of ocean colour data. The model is based on the observation that the absolute value of a_ph(443) co-varies with the spectral slope of phytoplankton absorption in the range of 443-510 nm, which is also a characteristic of phytoplankton size classes. The model when used for analysis of SeaWiFS global data, showed that picoplankton dominated ~ 79.1% of surface waters, nanoplankton ~ 18.5% and microplankton the remainder (2.3%). The N. and S. Atlantic and the N. and S. Pacific Oceans showed seasonal cycles with both micro and nanoplankton increasing in spring and summer in each hemisphere, while picoplankton, dominant in the oligotrophic gyres, decreased in the summer. The PSCs derived from SeaWiFS data were verified by comparing contemporary 8-day composites with PSCs derived from in situ pigment data from quasiconcurrent Atlantic Meridional Transect cruises.     

A multi-objective neural network based method for cover crop identification from remote sensed data

One of the objectives of conservation agriculture to reduce soil erosion in olive orchards is to protect the soil with cover crops between rows. Andalusian and European administrations have developed regulations to subsidise the establishment of cover crops between rows in olive orchards. Current methods to follow-up the cover crops systems by administrations consist of sampling and on ground visits of around 1% of the total olive orchards surface at any time from March to late June. This paper outlines a multi-objective neural network based method for the classification of olive trees (OT), bare soil (BS) and different cover crops (CC), using remote sensing data taken in spring and summer.The main findings of this paper are: (1) the proposed models performed well in all seasons (particularly during the summer, where only 48 pixels of CC are confused with BS and 10 of BS with CC with the best model obtained. This model obtained a 97.80% of global classification, 95.20% in the class with the worst classification rate and 0.9710 in the KAPPA statistics), and (2) the best-performing models could potentially decrease the number of complaints made to the Andalusian and European administrations. The complaints in question concern the poor performance of current on-ground methods to address the presence or absence of cover crops in olive orchards.     

夏玉米和冬小麦秸秆对石灰性土壤磷吸附特性及磷素形态的影响

本文对夏玉米秸秆(MR)和冬小麦秸秆(WR)单施或者与P肥混施(在等P量条件下)对石灰性土壤P的吸附特性及其形态转化进行了为期15周的室内模拟培养研究,结果表明,无论是MR和WR单施,还是秸秆与P肥混施,都可以减少土壤对P的吸附量,提高土壤P的活性,其中秸秆单施处理的活性无机磷(Pi)和有机磷(Po)(NaHCO3-P或者NaOH-P)提高较大,夏玉米秸秆单施时,比对照(CK)增加Pi、Po的量分别达6.0、5.6mgkg-1(NaHCO3-P),增加NaOH-Po为12.7mgkg-1。并通过Langmuir方程求得P的最大吸附量(b)、P吸附结合能常数(k)、P素最大缓冲量(MPBC)、标准需P量(SPR)的值,进一步说明了两种秸秆均可使土壤对P的吸附能力降低,增加土壤中P的活性。     

Space-borne study of seasonal,multi-year,and decadal phytoplankton dynamics in the Bay of Biscay

Seasonal and inter-annual variations in phytoplankton community abundance in the Bay of Biscay are studied. Preliminarily processed by the National Aeronautics and Space Administration (NASA) to yield normalized water-leaving radiance and the top-of-the-atmosphere solar radiance, Sea-viewing Wide Field-of-View Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS), and Coastal Zone Color Scanner (CZCS) data are further supplied to our dedicated retrieval algorithms to infer the sought for parameters. By applying the National Oceanic and Atmospheric Administration's (NOAA's) Advanced Very High Resolution Radiometer (AVHRR) data, the surface reflection coefficient in the only band in the visible spectrum is derived and employed for analysis. Decadal bridged time series of variations of diatom-dominated phytoplankton and green dinoflagellate Lepidodinium chlorophorum within the shelf zone and the coccolithophore Emiliania huxleyi in the pelagic area of the Bay are documented and analysed in terms of impacts of some biogeochemical and geophysical forcing factors.

It is shown that in the shelf zone of the Bay, the diatom-dominated phytoplankton community variations are predominantly controlled by river discharge variations, by water column stratification conditions (forming in winter–early spring), and by wind action (resulting in such phenomena as up-wellings and sediment re-suspension).

Satellite data indicate that while in river deltas and adjoining waters the L. chlorophorum blooming events occur annually, in the Iroise Sea and near the Bailiwick of Guernsey, they happen irregularly. It is thought that such an irregular pattern, possibly, arises from L. chlorophorum competing with other phytoplankton species for nutrients.

E miliania huxleyi blooms are found to occur nearly every year in the northern part of the Bay, whereas in the central area, this phenomenon occurs very irregularly. Satellite data indicate that variations in the water chemistry (variations in the nitrogen : phosphorus ratio due to preceding blooms of diatoms), and the incident irradiance level (degree of cloudiness), are important factors controlling the occurrence of E. huxleyi blooming in the central part of the Bay. Covering a 30 year period, the bridged data from CZCS, AVHRR, SeaWiFS, and MODIS imply that climate change might be responsible for the observed increase in E. huxleyi blooming events in the Bay since 1979.     

Sensitivity of the Indian Ocean circulation to phytoplankton forcing using an ocean model

Most ocean general circulation models (OGCMs) do not take into account the effect of space- and time-varying phytoplankton on solar radiation penetration, or do it in a simplistic way using a constant attenuation depth, even though one-dimensional experiments have shown potential significant effect of phytoplankton on mixed-layer dynamics. Since some ocean basins are biologically active, it is necessary for an OGCM to take water turbidity into account, even if it is not coupled with a biological model. Sensitivity experiments carried out with the Massachusetts Institute of Technology (MIT) OGCM with spatially and temporally-varying pigment concentration from Sea-viewing Wide Field-of-view Sensor (SeaWiFS) data during 1998-2003 reveal the effect of ocean turbidity on tropical Indian Ocean circulation. Variations of light-absorbing phytoplankton pigments change the vertical distribution of solar heating in the mixed layer, thereby affecting upper-ocean circulation. A simulation was performed from 1948 to 2003 with a constant minimum pigment concentration of 0.02 mg m^− 3 while another simulation was performed from September 1997 to December 2003 with variable pigment concentration, and the differences between these two simulations allow us to quantify the effects of phytoplankton on solar radiation penetration in the ocean model. Model results from a period of 6 years (1998-2003) show large seasonal variability in the strength of the meridional overturning circulation (MOC), meridional heat transports (MHT), and equatorial under current (EUC). The MOC mass transport changes by 2 to 5 Sv (1 Sv = 10⁶ m³ s^− 1) between boreal winter (January) and boreal summer (July), with a corresponding change in the MHT of ∼ 0.05 PW (1 PW = 10¹⁵ W) in boreal winter, which is close to the expected change associated with a significant climate change [Shell, K., Frouin, R., Nakamoto, S., & Somerville, R.C.J. (2003): Atmospheric response to solar radiation absorbed by phytoplankton. Journal of Geophysical Research, 108(D15), 4445. doi:10.1029/2003JD003440.]. In addition, changes in phytoplankton pigments concentration are associated with a reduction in the EUC by ∼ 3 cm s^− 1. We discuss the possible physical mechanisms behind this variability, and the necessity of including phytoplankton forcing in the OGCM.     

A differential-difference equations model of a dynamic aquatic ecosystem†

This paper presents a differential-difference equations model of a dynamic aquatic ecosystem. This paper departs from other models by considering : (a) specific phyla of phytoplankton, zooplankton and nekton ; (b) their prey—predation relationships ; (c) both allelochemic and antotoxic effects of algae upon zooplankton and other algae ; (d) inter-phyla competition for nutrients. Other factors included are : limiting effects of phosphates, nitrates, silicates, photoperiod, turbidity, temperature, and time lag, as they affect growth and reproduction of the biota. The model uses the western basin of Lake Erie as a test example, but any shallow basin that does not experience thermoclines could be used.     

Phytoplankton dynamics in the eastern Caribbean Sea as detected with space remote sensing

The Space Information Laboratory (SIL) of the Tropical Center for Earth and Space Studies of the University of Puerto Rico at Mayagüez (UPRM) has been collecting and processing satellite data since December of 1996. Satellite imagery from the Advanced Very High Resolution Radiometer (AVHRR) and the Sea viewing Wide Field of view Sensor (SeaWiFS) provides us with a new understanding of phytoplankton dynamics in the Caribbean region. SeaWiFS shows the intrusion of waters into the eastern Caribbean Sea from the Orinoco River during fall and from the Amazon River during spring–summer. Strong coastal upwelling in Venezuela produced by the trade winds during winter–spring is detected with the AVHRR. The satellite data suggest that these seasonal events may play an important role in phytoplankton fertilization of the eastern Caribbean Sea. SeaWiFS and hydrological data are also combined to evaluate the impact of hurricanes on phytoplankton distribution. The development of models for estimation of ocean primary productivity using SeaWiFS and AVHRR data is now in progress.     

Modeling the pathways and attenuation of nutrients from domestic wastewater treatment systems at a catchment scale

Domestic Wastewater Treatment Systems (DWTS) are often cited as significant sources of pollution in rural catchments. A mass balance based model has been developed to determine annual nutrient loading from individual DWTS into rivers in Ireland. The transport and attenuation of nitrogen and phosphorus in DWTS effluent to groundwater and surface water has been formulated using the results from field research in Ireland, as well as being informed by other international studies. Conceptually the model splits the transport of nutrients to the river into three pathways: direct to surface water (for areas of inadequate percolation), a near surface (subsoil) pathway, and a groundwater pathway. The model quantifies the net nutrient contribution for each DWTS and has been incorporated into a broader source load apportionment catchment model which includes agricultural inputs, thereby enabling the relative risk of nutrient pollution from DWTS in a catchment to be defined.     

A nitrogen spectral response model and nitrogen estimation of summer maize during the entire growth period

ABSTRACT

Timely and effective prediction of nitrogen content in summer maize could provide support data for precise fertilization. In this study, the feasibility and expansibility of predicting the nitrogen mechanism model of summer maize leaves through its entire growth period were investigated on the basis of the theory of leaf radiation transmission mechanism. A complete random test of data from two maize varieties and two nitrogen fertilizer applications in 2017 was conducted. Three versions of the leaf optical PROperties SPECTra (PROSPECT) model, namely, PROSPECT-4, PROSPECT-5, and PROSPECT-D were used to link the established leaf nitrogen density (LND) and chlorophyll-a + b (chl-a + b) models, that is, chl-a + b-LND model. A nitrogen response transfer model (N-RTM) was established by linking the optimal PROSPECT and chl-a + b-LND models. Results were as follows. (1) chl-a + b estimation using the PROSPECT-D model yielded the highest accuracy (the coefficient of determination (R²) = 0.774, the normalized root mean squared error (nRMSE) = 13.19%) among the three PROSPECT models, it shows that the model considering more factors can better reflect the internal law of blade, and could be used as the basic model of N-RTM; (2) Established chl-a + b-LND models based on the dataset from each growth stage showed differences using the confidence interval method, and the R² values of the optimal regression model at V12, VT, and R3 were 0.794, 0.781, and 0.821, respectively. Based on the changes of chl-a + b and LND during the growth period, a piecewise model was constructed; (3) The R² and nRMSE values between the measured and estimated LNDs were 0.656% and 22.86%, respectively. The validation results are better than the traditional empirical model. The results showed that the segmented model, which considered the interaction of various factors within the leaves and the change of chl-a + b-LND during the growth period, had better performance in nitrogen monitoring. The constructed nitrogen model in this study preliminarily realized the remote sensing prediction of the nitrogen mechanism model and had a certain mechanism.     

不同土壤层次供应水分和养分对玉米幼苗生长和吸收养分的影响

本试验模拟滴灌方法 ,在不同土壤层次进行灌水和施用氮磷养分的盆栽玉米试验 ,旨在探讨在不同土壤层次供应水分和养分对夏玉米幼苗生长、根系空间构型及玉米对养分吸收的影响。试验表明 :在土壤深层进行滴灌可以有效降低土面蒸发 ,提高水分和养分的利用效率 ,从而显著提高玉米幼苗的生长量 ;在不同层次施肥灌水 ,对玉米根系在土壤中的空间构型影响很大 ,进行深层滴灌可以极大促进根系在较深土壤中的发育 ;在不同土层施肥灌水对玉米幼苗吸收N、P、K三种养分的能力也有影响 ,深层施肥灌水提高了玉米对 3种养分的吸收量