The question of the limiting nutrient(s) for production of phytoplankton and macrophytes was explored in two contrasting freshwater systems receiving N- and P-rich mine effluents from the Boliden and Kiruna mine sites, northern Sweden. For both sites, total N (TN), total P (TP) and TN:TP mass ratios in water, sediment and macrophytes were used to examine (1) spatial variations within the systems, (2) differences between the systems and (3) seasonal variations. The TN concentration from the discharge point at the Kiruna site was about seven times higher than at the Boliden discharge point, while the TP concentration was 10 times lower than in the discharge point at the Boliden site. The majority of the studied lakes showed elevated biomass of phytoplankton, with maximum values found in Lake Bruträsket (Boliden). Mining activities have affected the nutrient regime of the two recipients by contributing to elevated TN and TP concentrations and TN:TP mass ratios as well as elevated production of phytoplankton and macrophytes compared to the reference sites. Depending on the NH4 concentration in the effluent at the Boliden site, water column TN:TP mass ratios shifted from being >22, indicating P-deficiency, to between 9 and 22, indicating a transition from N- to P-deficiency (co-limitation). However, water column TN:TP mass ratios at the Kiruna site always indicated P-deficiency, while TN:TP mass ratios of macrophytes indicate that both sites may vary from N- to P-limitation. The study suggests that for the design of efficient monitoring programmes and remediation measures, it is important to consider the major N and P species in water, phytoplankton, sediment and macrophytes.

This paper presents a biogeochemical model developed for a clarification pond receiving ammonium nitrogen rich discharge water from the Boliden concentration plant located in northern Sweden. Present knowledge about nitrogen (N) transformations in lakes is compiled in a dynamic model that calculates concentrations of the six N species (state variables) ammonium-N (Nam), nitrate-N (Nox), dissolved organic N in water (Norg), N in phytoplankton (Npp), in macrophytes (Nmp) and in sediment (Nsed). It also simulates the rate of 16 N transformation processes occurring in the water column and sediment as well as water–sediment and water–atmosphere interactions. The model was programmed in the software Powersim using 2008 data, whilst validation was performed using data from 2006 to 2007. The sensitivity analysis showed that the state variables are most sensitive to changes in the coefficients related to the temperature dependence of the transformation processes. A six-year simulation of Nam showed stable behaviour over time. The calibrated model rendered coefficients of determination (R2) of 0.93, 0.79 and 0.86 for Nam, Nox and Norg, respectively. Performance measures quantitatively expressing the deviation between modelled and measured data resulted in values close to zero, indicating a stable model structure. The simulated denitrification rate was on average five times higher than the ammonia volatilisation rate and about three times higher than the permanent burial of Nsed and, hence, the most important process for the permanent removal of N. The model can be used to simulate possible measures to reduce the nitrogen load and, after some modification and recalibration, it can be applied at other mine sites affected by N rich effluents.

Littoral interactions among sediment, water and macrophytes are poorly understood. In particular there is a gap in knowledge concerning the importance of macrophytes as sinks and sources of trace elements. Such knowledge is however central for, amongst others, explaining potential mechanisms behind the community structure of macrophytes and for the development of macrophyte-based indicator values. We studied the interactions between the three matrices (sediment, water and macrophytes) at 19 sampling sites in Storträsket, a 1.7 km2 boreal lake at the land uplift coast of Northern Sweden in summer 2008. The catchment of Storträsket was dominated  by coniferous forest of mainly the dwarf-shrub type and open wet mires. The upper sediment layers (0-6 cm) were dominated by fine detritus. Fine detritus dominated also the lower layers (>6 cm but ≤10 cm) at all but four of the studied localities where fine sediments (particle diameter <0.2 mm) dominated. Sediment and water element concentrations were related to element concentrations in the dominating macrophyte species, viz. Nuphar lutea (roots and leaves), Potamogeton natans (leaves) and Sparganium angustifolium (leaves) and to chlorophyll concentrations using uni- and multivariate statistics. We studied 27 major and trace elements. Estimations of abundance and biomass of N. lutea in eight bays was based on the evaluation of high resolution (2 cm) aerial photographs. The total biomass of N. lutea and standardized biomass (biomass per unit of area) differed significantly among bays. Also concentrations in all matrices as well as in chlorophyll showed significant spatial variation in the lake. N. lutea showed for several elements significant partitioning of elements between roots and leaves (e.g. Ca, K, Na, Fe, Pb, Zn). Correlations between element concentrations in sediment/water and in macrophytes were in general weak but significant for amongst others Si in water and leaves of P. natans and Co, Cu and Fe in water and roots of N. lutea. Interpreting correlations of elements between the sediment and macrophytes might in our study be impeded by potential incorporation of lithogenic material in extracellular macrophyte tissue. Our study identified especially N. lutea as a major sink (during vegetation period) and source (during autumn and winter) of several major and trace elements. Interactions between the matrices, chlorophyll concentrations and macrophyte community structure are further discussed as well as the implications of our results for the development of macrophyte-based indicator values.

Vegetation in and along aquatic systems has important regulatory and ecological functions. Aquatic vegetation is also frequently used as an indicator of environmental conditions. To enhance our knowledge of the complex natural processes in the littoral zone, i.e., the zone from the high water mark to the lower limit of aquatic vegetation, it is critical to assess plant occurrence and abundance at the species level. This assessment is traditionally performed with labour-intensive field methods. Recently developed remote sensing systems with unmanned aircrafts that take aerial images at low flying height, offer new possibilities for surveying aquatic and riparian vegetation. Unmanned aerial systems (UASs) produce aerial images with sub-decimetre spatial resolution and high spatial accuracy at low cost and are highly flexible in time and space. The goal of this thesis was to evaluate the potential of an UAS for surveying non-submerged aquatic and riparian vegetation, including the identification of plants at the species level and vegetation mapping. Based on produced vegetation maps and field sampling, we also assessed the total biomass of entire riparian zones (320-m river stretches) and the biomass and trace metal content of dominant species along a pollution gradient. In total, the UAS was tested in four aquatic systems, two lakes and two rivers, in boreal northern Sweden. Generated orthoimages were interpreted visually. The spatial resolution varied from 5–5.6 cm. At two test sites we identified plant species with high accuracy (94.6 and 80.4% for aquatic and riparian vegetation, respectively). Prior knowledge on locally occurring species was necessary for correct species identification. The time needed for manual vegetation mapping increased with increasing vegetation complexity. At the test site for biomass assessment, biomass and trace element (Cu, Cd, and Zn) contents varied considerably between species. Salix sp. (willows) comprised only 3% of the total dominant-species biomass but contained 73% of all Cd and 24% of all Zn. In contrast, Carex rostrata/vesicaria (bottle and blister sedge) comprised 80% of the total biomass and contained 85% of all Cu and 66% of all Zn. This result emphasizes the need for species-specific assessment, for example, in planning of phytoremediation measures. The tested UAS facilitates species-level surveying and mapping of non-submerged aquatic and riparian vegetation and can be used in combination with field sampling to accurately assess biomass and the amount of accumulated contaminants at the scale of entire riparian zones. The main future challenge will be to identify/develop automated methods for vegetation mapping which successfully cope with the inherent complexity of the orthoimages generated with the presented UAS.

QuestionsDo high-resolution (sub-decimetre) aerial images taken with unmanned aircraft systems (UASs) allow a human interpreter to recognize aquatic plant species? Can UAS images be used to (1) produce vegetation maps at the species level; and (2) estimate species abundance? LocationOne river and two lake test sites in northern Sweden, middle boreal sub-zone. MethodsAt one lake and at the river site we evaluated accuracy with which aquatic plant species can be identified on printouts of UAS images (scale 1:800, resolution 5.6 cm). As assessment units we used homogeneous vegetation patches, referred to as vegetation stands of one or more species. The accuracy assessment included calibration and validation based on field controls. At the river site, we produced a digital vegetation map based on an UAS orthoimage (geometrically corrected image mosaic) and the results of the species identification evaluation. We applied visual image interpretation and manual mapping. At one of the lake sites, we assessed the abundance (four-grade scale) of the dominating Phragmites australis and produced a cover map. ResultsWe identified the species composition of vegetation stands at the lake and the river site with an overall accuracy of 95.1% and 80.4%, respectively. It was feasible to produce a digital vegetation map, albeit with a slight reduction in detail compared to the species identification step. At the site for abundance assessment, P. australis covered 20% of the total lake surface area, and 70% of the covered area had cover ≤25%. ConclusionsThe tested UAS facilitates lake and river vegetation identification and mapping at the species level, as well as abundance estimates

Quantifying plant biomass and related processes such as element allocation is a major challenge at the scale of entire riparian zones. We applied sub-decimetre-resolution (5 cm) remote sensing using an unmanned aircraft system (UAS) in combination with field sampling to quantify riparian vegetation biomass at three locations (320-m river stretches) along a mining-impacted boreal river and estimated the amounts of Cd, Cu, and Zn stored in the dominant species. A species-level vegetation map was derived from visual interpretation of aerial images acquired using the UAS and field sampling to determine species composition and cover. Herbaceous and shrub biomass and metal contents were assessed by combining the vegetation maps with field sampling results. Riparian zone productivity decreased from 9.5 to 5.4 t ha-1 with increasing distance from the source of contamination, and the total amount of vegetation-bound Cd and Zn decreased from 24 to 0.4 and 3,488 to 211 g, respectively. Most Cu was stored at the central location. Biomass and metal contents indicated large variation between species. Salix spp. comprised only 17% of the total dominant-species biomass but contained 95% of all Cd and 65% of all Zn. In contrast, Carex rostrata/vesicaria comprised 64% of the total dominant-species biomass and contained 63% of all Cu and 25% of all Zn. Our study demonstrates the applicability of UAS for monitoring entire riparian zones. The method offers great potential for accurately assessing nutrient and trace element cycling in the riparian zone and for planning potential phytoremediation measures in polluted areas