ABSTRACT
Remote sensing using satellite imagery has been promoted as a method to broaden the scale and frequency of cyanobacterial monitoring. This relies on the ability to establish relationships between the reflectance spectra of water bodies and the abundance of cyanobacteria. A challenge to achieving this comes from a limited understanding of the extent to which the optical properties of cyanobacteria vary according to their physiological state and growth environment. The aim of the present study was to determine how growth stage, nutrient status and irradiance affect pigment concentrations and absorption spectra in two common bloom forming cyanobacterial taxa: Dolichospermum lemmermannii and Microcystis aeruginosa. Each species was grown in laboratory batch culture under a full factorial design of low or high light intensity and low, medium, or high nitrate concentrations. Absorption spectra, pigment concentrations and cell density were measured throughout the growth phases. The absorption spectra were all highly distinguishable from each other, with greater interspecific than intraspecific differences, indicating that both D. lemmermannii and M. aeruginosa can be readily differentiated using hyperspectral absorption spectra. Despite this, each species exhibited different responses in the per-cell pigment concentrations with varying light intensity and nitrate exposure. Variability among treatments was considerably higher in D. lemmermannii than in M. aeruginosa, which exhibited smaller changes in pigment concentrations among the treatments. These results highlight the need to understand the physiology of the cyanobacteria and to take caution when estimating biovolumes from reflectance spectra when species composition and growth stage are unknown.
Subject(s)
Cyanobacteria , Microcystis , Nitrates , Nutrients , Batch Cell Culture TechniquesABSTRACT
Coastal lakes, also known as temporarily open/closed estuaries or intermittently closed and open lakes and lagoons, are common worldwide, are typically sites of high biodiversity and often contain abundant macrophyte populations. Anthropogenic stressors such as increased nutrient and sediment loading have adverse effects on submerged macrophytes, and when closed, the lack of tidal flushing makes coastal lakes highly susceptible to eutrophication. Lake openings to the sea may occur naturally, but many coastal lakes are also opened artificially, often to reduce inundation of surrounding land. Here we used a coupled hydrodynamic-ecological model (DYRESM-CAEDYM), modified to include dynamic feedback between submerged macrophyte biomass and sediment resuspension, to explore the interactive effects of multiple disturbances (openings, eutrophication and climate change) on the dynamics of primary producers in a coastal lake (Waituna Lagoon) in South Island, New Zealand. Our results indicate that with exposure to high external nutrient loads, the frequent disturbances caused by artificial openings prevent sustained dominance by algae (algal biomass averaged 192 g C m-2 with artificial openings compared to 453 g C m-2 with no openings). However, under current nutrient loading, climate change is likely to enhance the effects of eutrophication on the system (algal biomass averaged 227 g C m-2 with climate change compared with 192 g C m-2 for current climate). The model provides a decision-support tool to guide lake management in setting limits for nutrient loads and managing the opening regime, in order to prevent eutrophication and the potential collapse of the macrophyte community.
Subject(s)
Climate Change , Eutrophication , Lakes , Ecosystem , New Zealand , PhosphorusABSTRACT
The concentration of chlorophyll a (chl a; as a proxy for phytoplankton biomass) provides an indication of the water quality and ecosystem health of lakes. An automated image processing method for Landsat images was used to derive chl a concentrations in 12 Rotorua lakes of North Island, New Zealand, with widely varying trophic status. Semi-analytical and empirical models were used to process 137 Landsat 7 Enhanced Thematic Mapper (ETM+) images using records from 1999 to 2013. Atmospheric correction used radiative transfer modelling, with atmospheric conditions prescribed with Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and AIRS data. The best-performing semi-analytical and empirical equations resulted in similar levels of variation explained (r (2) = 0.68 for both equations) and root-mean-square error (RMSE = 10.69 and 10.43 µg L(-1), respectively) between observed and estimated chl a. However, the symbolic regression algorithm performed better for chl a concentrations <5 µg L(-1). Our Landsat-based algorithms provide a valuable method for synoptic assessments of chl a across the 12 lakes in this region. They also provide a basis for assessing changes in chl a individual lakes through time. Our methods provide a basis for cost-effective hindcasting of lake trophic status at a regional scale, informing on spatial variability of chl a within and between lakes.
Subject(s)
Chlorophyll/analysis , Environmental Monitoring/methods , Lakes/chemistry , Phytoplankton/growth & development , Water Quality , Algorithms , Biomass , Chlorophyll A , Ecosystem , Models, Theoretical , New Zealand , Satellite ImageryABSTRACT
Global environmental change has influenced lake surface temperatures, a key driver of ecosystem structure and function. Recent studies have suggested significant warming of water temperatures in individual lakes across many different regions around the world. However, the spatial and temporal coherence associated with the magnitude of these trends remains unclear. Thus, a global data set of water temperature is required to understand and synthesize global, long-term trends in surface water temperatures of inland bodies of water. We assembled a database of summer lake surface temperatures for 291 lakes collected in situ and/or by satellites for the period 1985-2009. In addition, corresponding climatic drivers (air temperatures, solar radiation, and cloud cover) and geomorphometric characteristics (latitude, longitude, elevation, lake surface area, maximum depth, mean depth, and volume) that influence lake surface temperatures were compiled for each lake. This unique dataset offers an invaluable baseline perspective on global-scale lake thermal conditions as environmental change continues.
ABSTRACT
While expansion of agricultural land area and intensification of agricultural practices through irrigation and fertilizer use can bring many benefits to communities, intensifying land use also causes more contaminants, such as nutrients and pesticides, to enter rivers, lakes, and groundwater. For lakes such as Benmore in the Waitaki catchment, South Island, New Zealand, an area which is currently undergoing agricultural intensification, this could potentially lead to marked degradation of water clarity as well as effects on ecological, recreational, commercial, and tourism values. We undertook a modeling study to demonstrate science-based options for consideration of agricultural intensification in the catchment of Lake Benmore. Based on model simulations of a range of potential future nutrient loadings, it is clear that different areas within Lake Benmore may respond differently to increased nutrient loadings. A western arm (Ahuriri) could be most severely affected by land-use changes and associated increases in nutrient loadings. Lake-wide annual averages of an eutrophication indicator, the trophic level index (TLI) were derived from simulated chlorophyll a, total nitrogen, and total phosphorus concentrations. Results suggest that the lake will shift from oligotrophic (TLI = 2-3) to eutrophic (TLI = 4-5) as external loadings are increased eightfold over current baseline loads, corresponding to the potential land-use intensification in the catchment. This study provides a basis for use of model results in a decision-making process by outlining the environmental consequences of a series of land-use management options, and quantifying nutrient load limits needed to achieve defined trophic state objectives.
Subject(s)
Decision Support Techniques , Models, Theoretical , Water Quality , Agriculture , Chlorophyll/analysis , Chlorophyll A , Eutrophication , Lakes , New Zealand , Nitrogen/analysis , Phosphorus/analysis , Phytoplankton/growth & development , Water Pollutants, Chemical/analysisABSTRACT
Cost-effective monitoring is necessary for all investigations of lake ecosystem responses to perturbations and long-term change. Satellite imagery offers the opportunity to extend low-cost monitoring and to examine spatial and temporal variability in water clarity data. We have developed automated procedures using Landsat imagery to estimate total suspended sediments (TSS), turbidity (TURB) in nephlometric turbidity units (NTU) and Secchi disc transparency (SDT) in 34 shallow lakes in the Waikato region, New Zealand, over a 10-year time span. Fifty-three Landsat 7 Enhanced Thematic Mapper Plus images captured between January 2000 and March 2009 were used for the analysis, six of which were captured within 24 h of physical in situ measurements for each of 10 shallow lakes. This gave 32-36 usable data points for the regressions between surface reflectance signatures and in situ measurements, which yielded r (2) values ranging from 0.67 to 0.94 for the three water clarity variables. Using these regressions, a series of Arc Macro Language scripts were developed to automate image preparation and water clarity analysis. Minimum and maximum in situ measurements corresponding to the six images were 2 and 344 mg/L for TSS, 75 and 275 NTU for TURB, and 0.05 and 3.04 m for SDT. Remotely sensed water clarity estimates showed good agreement with temporal patterns and trends in monitored lakes and we have extended water clarity datasets to previously unmonitored lakes. High spatial variability of TSS and water clarity within some lakes was apparent, highlighting the importance of localised inputs and processes affecting lake clarity. Moreover, remote sensing can give a whole lake view of water quality, which is very difficult to achieve by in situ point measurements.