Static Aquatic Mesocosms Workshop 'In-situ trialing for ecological and chemical studies in support of WFD implementation' May Palais Beaumont Pau - France Dr. Hector Galicia, CEO Innovative Environmental Services (IES) Ltd., Switzerland

Outdoor Mesocosms  Aquatic model ecosystems from 1 to 10 4 m 3  Exposure from days to months  Similarity to natural ecosystems is moderate to high  Organisms included:  Primary producers (algae, periphyton),  Invertebrate herbivores and consumers,  Macrophytes  Fish only if separate

Outdoor Mesocosms  Variables and End Points  Weather conditions  Water quality parameters: pH, alkalinity, hardness, temperature, dissolved oxygen, solar radiation  Mortality, growth, reproduction, diversity, abundance, photosynthesis, composition of populations, recovery, concentration, rate of disappearance and degradation, metabolites Important tool to help understanding and predicting what may occur in the natural environment. More details e.g. OECD No. 53, Guidance Document on Simulated Freshwater Lentic Field Tests (Outdoor Microcosms and Mesocosms) (2006) S. Maise, Natural Variability of Zooplankton and Phytoplankton in Outdoor Aquatic Microcosms.

MESOCOSM FACILITY DESIGN The design of the testing facility determines the level of replication, and realism available for a studyThe design of the testing facility determines the level of replication, and realism available for a study Mainly two different systems exist:Mainly two different systems exist: –A set of separate identical tanks, which are all connected to a mixing tank or lagoon or small natural pond Homogeneous starting conditions are achieved by water circulation via the mixing tankHomogeneous starting conditions are achieved by water circulation via the mixing tank –A big basin as a host for identical enclosures Enclosures are equivalent to isolated tanks and are placed into the host basin shortly before test start to provide similar starting conditionsEnclosures are equivalent to isolated tanks and are placed into the host basin shortly before test start to provide similar starting conditions

Separate Tanks-Type MES Facility Syngenta’s Facility in Stein, Switzerland 1. From Maise S., Galicia, H. F., Gonzalez-Valero, J. F., and Huber, W., 1998 IUPAC

Outdoor Enclosure Type MES Facility Springborn Smithers Outdoor Facility in Horn (SSLEU), Switzerland. Gratefully acknowledged

Mesocosms Simulating Shallow Waters Systems 20 cm Natural Sediment Surface Film Sampling (Grid) Water Sampling at different depths 1 to 10 m 3 Natural Water from e.g. a lake or river Macrophytes Sediment Organisms Aquatic Organisms Or Fish ‘alone’

Natural Sediment & Water Enclosure Type System 3.5 m 3 SSLEU Facility, Switzerland. Gratefully acknowledged.

Upper View SSLEU Facility, Switzerland. Gratefully acknowledged.

Mesocosm Studies: Evolution in Time Concept Early 1980’s Late 1990’s Volume (m3) 2 to to 20 No. of Concentrations 3* 4 to 6 Total Tanks/Enclosures 4 to 12* 12 to 30 Experimental Design ANOVA And / or Linear Regression Dose Validation RarelyOften Active Substance 14 C less common 14 C more common Statistical Evaluation Single variable ANOVA, Replicated regression or EC x determination, Multivariate * : Most studies during this time were restricted to a 12 pond experimental design, the minimum recommended by the EPA guidelines (Touart, 1988). Later on called the US-EPA design. * : Most studies during this time were restricted to a 12 pond experimental design, the minimum recommended by the EPA guidelines (Touart, 1988). Later on called the US-EPA design.

MES: Evolution in Time (Continued) Concept Early 1980’s Late 1990’s Environ. Compartment All Problem Specific Environmental Fate Could not be done Done if adequate End Points Lack of agreement Achievable & Evolving Regulatory interpretation MES found inadequate (US-EPA dropped its requirement in 1992) Agreed & Evolving Recovery Designs Indirect Fit for purpose Re-colonisationIndirectNatural/Design (Based on the above) Uncertainty in Results Larger, not fully assessed Lower, and more fully assessed

Objectives of Mesocosm Studies  Provide with more knowledge about the ecological relevance of effects identified in laboratory studies  Studies include a variety of species, functional groups or habitat types  Studies focus on effects at the community and ecosystem level, potential indirect effects and the recovery potential of sensitive organisms  Allow to measure effects of a chemical under more environmentally realistic exposure conditions i.e. in the presence of  Light and  Matrices such as Macrophytes, Natural Sediment and Water, Suspended Organic Matter  Formation of surface film and natural circulation during the day  More realistic habitat for aquatic species  Enables the study of the impact on the structural and functional attributes of natural ecosystem (SETAC guidance document, 1994; OECD Draft Guidelines)

End Points in Mesocosms Testing ‘TYPICAL’ 1. Quality: Water and Sediment 2. Effects on: Phytoplankton, Periphyton, Macrophytes, Macro-Invertebrates, Zooplankton, Fish 3. Residues usually in water and sediment NOT SO ‘TYPICAL’ 1. Rate of degradation and metabolism ( 14 -C) 2. Bioaccumulation 3. Residue Biomagnification (feeding studies) 4. Distribution of substances in the water column (concentration as a function of water depth or stratification) 5. Concentration of lipophylic substances in the surface film

PRC DIAGRAM

NATURAL VARIABILITY  It is defined as the complexity and variability of system properties e.g. nutrients, species abundance, and heterogeneity, in space  Natural communities are characterized as:  spatially heterogeneous at any scale of resolution  dynamic systems, with population densities and relative abundances of species changing with time  Spatial heterogeneity is related to heterogeneous environmental conditions as well as to population dynamics

NATURAL VARIABILITY and EXPERIMENTAL UNCERTAINTY TOTAL VARIABILITY = f[Natural Variability (Life-cycle, Time in the season, Habitat Function, Life-phases, Natural Disturbances), Uncertainty due to Sampling Procedures, Uncertainty due to Analytical Procedures, Uncertainty due to Timing of the Sampling, Uncertainty due to Acute Effects, Uncertainty due to Chronic Effects] Life-phases, Natural Disturbances), Uncertainty due to Sampling Procedures, Uncertainty due to Analytical Procedures, Uncertainty due to Timing of the Sampling, Uncertainty due to Acute Effects, Uncertainty due to Chronic Effects]

Example of Coefficients of Variation for CONTROL Zooplankton (Separate-Tanks Facility Type) Maise, Susanne, 2001

Maximum Densities per Litre of Zooplankton in CONTROL Ponds for three Years Maise, Susanne, 2001

The level of replication (1) The level of replication (1) By Anova. C.V. range: 10% to 100%;  = 0.05 one-tailed Galicia, H., 2000

The level of replication (2) The level of replication (2) By ANOVA C.V.= 80% ;  = 0.05, one-tailed Galicia, H., 2000

NATURAL VARIABILITY Some Conclusions from our Research Work The range of system-inherent variability of  Zooplankton and  Phytoplankton is comparable to the variability in natural ecosystems  Variability was dominated by seasonality, similar to natural ecosystems  Pesticide effects were best detected using  Multivariate statistics in combination with  Univariate methods and  Graphical presentation

Control Variation with respect to Treated Enclosures HGF

Experimental Design Some Conclusions from our Research Work For a MES with 3-4 replicates it is advisable toFor a MES with 3-4 replicates it is advisable to –Interpret results with great caution for those species which occur at mean densities below 10/L and –are represented in less than 50% of the replicates at a certain time point For species which are usually found near the critical limit values (cf. above), consider:For species which are usually found near the critical limit values (cf. above), consider: – changing the sampling strategy and – changing the design for counting the samples

Final Remarks  MIS is an effective test system to detect changes to the community structure of aquatic ecosystems and allows the investigation of secondary effects  Limitations:  concerning the detection and  interpretation of effects and  recovery for species occurring at low population densities,  which may be attributed to the low replication in MIS  to the seasonality of species groups  Overcome using the appropriate statistical tools or grouping the data at higher taxonomic levels.

THANK YOU VERY MUCH FOR LISTENING Questions? List of References:

Validation is possible because the repeated sampling allows comparison wrt to passive samplers - Biomarkers? - Experimentally controlled conditions including turbulence - Cost reduction by monitoring several substances simultaneously - 14C-substance can be used to verify results more easily for certain substances - Replication for statistical power is easy to achieve - Several concentrations to determine validity range Validation is possible because the repeated sampling allows comparison wrt to passive samplers - Biomarkers? - Experimentally controlled conditions including turbulence - Cost reduction by monitoring several substances simultaneously - 14C-substance can be used to verify results more easily for certain substances - Replication for statistical power is easy to achieve - Several concentrations to determine validity range Remarks Regarding Validation