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Patchiness is a typical property of water quality in lakes. However, in conventional water quality monitoring, patchiness is usually too expensive to take into account, due to the high number of required samples. This study examines a feasible methodology developed for estimating the representativeness of discrete chlorophyll a measurements. Four spatially extensive data sets were collected from the Enonselkä basin of Lake Vesijärvi in Southern Finland, using a flow trough system with a fluorometer in a moving boat. Data sets were used to estimate (1) the spatial representativeness of discrete sampling; (2) the effect of varying sample size on the detected mean chlorophyll a concentration and on the observed proportion of variance. Spatial representativeness was assessed using semivariogram analysis. Results indicate that the spatial representativeness of discrete sampling can remain undesirably low. Furthermore, in monitoring programs involving just one or only a few samples, there is a significant risk of obtaining a false estimate for the mean value and variance of chlorophyll a concentration over the whole monitoring area.

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1. The biomanipulation of Lake Vesij€ arvi in southern Finland putatively changed the lake ecosystem resulting in a clear-water state, but the dynamics behind the observed change remained unverified. 2. We used a general analytical approach to identify abrupt transitions in the long-term monitoring data of Lake Vesij€ arvi. Methods included the identification of breakpoints in chlorophyll a (response variable), in total phosphorus (TP; key driver) and in large-bodied cladocerans (feedback mechanism of biomanipulation). In addition, we characterised the frequency distribution and temporal variance of the response variable, as well as the interaction between TP and chlorophyll a. 3. According to long-term records, biomanipulation resulted in two distinct states: (i) a eutrophic state, where chlorophyll a and TP were linearly correlated and (ii) a mesotrophic state, where the key driver and response variables were not significantly correlated. The changed relationship between the key driver and response variables, together with the increase in the body size of cladocerans, suggested a hysteresis-type transition phase. However, the frequency distribution and the temporal variance of chlorophyll a agreed also with a threshold-type of transition. 4. Zooplankton seemed to be more important in maintaining the clear-water state than previously reported. Our results highlight the role of long-term monitoring data and the characterisation of abrupt transitions in ecosystem interactions as tools for sustainable management of lake ecosystems.

The effectiveness of different monitoring methods in detecting temporal changes in water quality depends on the achievable sampling intervals, and how these relate to the extent of temporal variation. However, water quality sampling frequencies are rarely adjusted to the actual variation of the monitoring area. Manual sampling, for example, is often limited by the level of funding and not by the optimal timing to take samples. Restrictions in monitoring methods therefore often determine their ability to estimate the true mean and variance values for a certain time period or season. Consequently, we estimated how different sampling intervals determine the mean and standard deviation in a specific monitoring area by using high frequency data from in situ automated monitoring stations. Raw fluorescence measurements of chlorophyll a for three automated monitoring stations were calibrated by using phycocyanin fluorescence measurements and chlorophyll a analyzed from manual water samples in a laboratory. A moving block bootstrap simulation was then used to estimate the standard errors of the mean and standard deviations for different sample sizes. Our results showed that in a temperate, meso-eutrophic lake, relatively high errors in seasonal statistics can be expected from monthly sampling. Moreover, weekly sampling yielded relatively small accuracy benefits compared to a fortnightly sampling. The presented method for temporal representation analysis can be used as a tool in sampling design by adjusting the sampling interval to suit the actual temporal variation in the monitoring area, in addition to being used for estimating the usefulness of previously collected data.

We report on preparatory work to develop a virtual laboratory for ecosystem services, ESLab, and demonstrate its pilot application in southern Finland. The themes included in the pilot are related to biodiversity conservation, climate mitigation and eutrophication mitigation. ESLab is a research environment for ecosystem services (ES), which considers ES indicators at different landscape scales: habitats, catchments and municipalities and shares the results by a service that utilizes machine readable interfaces. The study area of the pilot application is situated in the boreal region of southern Finland and covers 14 municipalities and ten catchments including forested, agricultural and nature conservation areas. We present case studies including: present carbon budgets of natural ecosystems; future carbon budgets with and without the removal of harvest residues for bioenergy production; and total phosphorus and nitrogen future loads under climate and agricultural yield and price scenarios. The ESLab allows researchers to present and share the results as visual maps, statistics and graphs. Our further aim is to provide a toolbox of easily accessible virtual services for ES researchers, to illustrate the comprehensive societal consequences of multiple decisions (e.g. concerning land use, fertilisation or harvesting) in a changing environment (climate, deposition).

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