Using the past to predict the future: lake sediments and the modelling of limnological disturbance

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<ul><li><p>ELSEVIER Ecological Modelling 78 (1995) 149-172 </p><p>E(OLO61(IIL mODELLIn6 </p><p>Using the past to predict the future: lake sediments and the modelling of limnological disturbance </p><p>N. John Anderson Geobotany Division, Geological Survey of Denmark, Thoravej 8, DK-2400 Copenhagen NV, Denmark </p><p>Received 1 July 1993; accepted 30 March 1994 </p><p>Abstract </p><p>Most lakes have been disturbed to varying degrees but for an individual lake the timescale of these disturbances is rarely known. Lake sediments, however, can be used as natural archives of perturbation histories, e.g. acidification and eutrophication. At present the use of simple weighted averaging models permits the reconstruction of a variety of water chemical variables from diatom and other microfossils preserved in lake sediments (pH, total phosphorus, salinity and lakewater temperature). Sediment records can, therefore, provide lake-specific background data for lake management as well as information about their ecological histories. The common models used in palaeolimnology (dating, transfer-functions) are reviewed and their role in environmental monitoring discussed. </p><p>Predictions of future lake water quality following lake restoration methods tend to be made from dynamic mathematical models, but they are also used for hindcasting (e.g. the MAGIC model of catchment acidification). A problem with using dynamic models is that they are often site-specific and require calibration for a given lake. Combined with reliable dating, chemical reconstructions from microfossil-based transfer functions offer the possibil- ity of testing hindcast predictions derived from dynamic mathematical models, e.g. for salinity, TP and pH. In this way, sediment microfossil-based models can assist with the parameterization of more complex, dynamic models of contemporary processes. In this review, comparisons between the two approaches (sediment-based and dynamic models) are given and possible future interactions outlined. Validation of mathematical models by palaeolimnologi- cal data might enhance their predictive ability when used for forecasting lake recovery. There is clearly, however, a need for a more rigorous approach to palaeolimnology, i.e. critical hypothesis generation. Multidisciplinary studies of lake disturbance, that combine palaeolimnology, dynamic modelling and contemporary process studies, would also be beneficial. </p><p>Keywords: Diatoms; Disturbance; History; Paleoclimatic reconstructions; Sediments; Water quality </p><p>1. Introduction </p><p>The importance of long-term temporal per- spectives to assist in the understanding of con- temporary environmental change and processes is now generally accepted by limnologists (e.g. Kitchell et al., 1988; Reynolds, 1990). Few lakes, </p><p>however, have been monitored continuously for long time-periods (for a notable exception, see Talling and Heany, 1988) and, modern experi- mental work with mesocosms covers only short time-periods (months to a few years). Similarly, whole-lake perturbations, while more realistic in that they involve the response of a number of </p><p>0304-3800/95/$09.50 1995 Elsevier Science B.V. All rights reserved SSDI 0304-3800(94)00124-Z </p></li><li><p>150 N.J. Anderson /Ecological Modelling 78 (1995) 149-172 </p><p>trophic levels, are normally temporally com- pressed in relation to natural disturbance rates or even anthropogenic perturbation; compare, for example, the timescales of Schindler et al. (1985) with those of Renberg et al. (1993). </p><p>The importance of relevant temporal perspec- tives has meant that lake sediment records are increasingly being used to provide information about recent (e.g. post-1800) rates of change and natural background conditions in lakes (Smol, 1992; Anderson, 1993). It is now possible to re- construct histories of both primary producers (di- atoms, chrysophytes, non-siliceous algae from pigments records) and higher trophic levels (zoo- plankton, chironomids), together with a number of water chemistry variables (pH, salinity, TP; see below). Importantly, a better understanding of the limitations of the sediment record due to depositional processes, as well as the range of temporal resolution offered by sediment records has meant that palaeolimnology is a substantial tool for monitoring environmental change (Anderson and Battarbee, 1994). </p><p>1.1. Ecosystem disturbance </p><p>Man has substantially altered his environment over a variety of timescales ( &lt; 101 to &gt; 103 years) and, therefore, palaeoecological methods are in- creasingly being used to provide information about past-conditions (Schoonmaker and Foster, 1991; Anderson and Battarbee, 1994). Ford (1989) outlined a number of factors that have direct relevance to both defining and understanding ecosystem disturbance: first, a thorough knowl- edge of baseline conditions; second, reliable defi- nitions of natural variability; third, when did the system begin to change; and fourth, the range of possible future trajectories. A temporal compo- nent is implicit to all these factors. </p><p>Smol (1992) suggested that there are four main ways of determining the four criteria defined above: i. direct historical measurements; ii. space- for-time substitution; iii. hindcasts using dynamic and empirical models; and iv. palaeolimnological reconstructions. As few lakes have been exten- sively monitored, most management decisions have to be based upon the latter three ap- </p><p>proaches. Palaeoecological techniques can be used in conjunction with normal space-for-time approaches to provide a more reliable temporal component (Pickett, 1989). Problems of inter-lake variability and regional pollution (which make it more difficult to identify pristine conditions in a given region) suggest that space-for-time ap- proaches will not always provide adequate restoration scenarios, in defining how far a par- ticular lake has shifted from its presumed "natu- ral background" state. Temporally dynamic records of changing environmental situations for a given lake are more useful for management purposes. </p><p>The use of empirical models for hindcasting are largely only extensions of the space-for-time approach, because they are based upon contem- porary regional relationships (e.g. between total phosphorus and chlorophyll). The use of dynamic models to provide historical reconstructions of chemical variables and/or ecosystem trajectories has become more common in a number of areas of environmental research (climate, acidification, and eutrophication). There have, however, been relatively few attempts to validate these long-term hindcasts. Recent progress in palaeolimnology has now provided means of defining background con- ditions in lakes, their disturbance histories and temporal scales of natural variability (Anderson and Battarbee, 1994). It has also given modellers a means of independent validation of their hind- cast reconstructions. </p><p>This paper concentrates on a number of areas related to the use of simple models in palaeolim- nology, as well as their relevance to the use and assessment of complex mathematical models in limnology. The first part of the paper deals with simple models in palaeolimnology and their vali- dation by contemporary monitoring data. The second part reviews the role of palaeolimnologi- cal records as independent test data for predic- tions and hindcasts derived from dynamic models. The final section suggests some possible future developments in sediment-based studies. For a description of recent trends and developments in palaeolimnology, see Smol (1990), Battarbee (1991), Anderson (1993) and Anderson and Bat- tarbee (1994). </p></li><li><p>N.J. Anderson/Ecological Modelling 78 (1995) 149-172 151 </p><p>2. Models in palaeolimnology </p><p>Until recently, palaeolimnology did not use modelling as an aid to the interpretation and understanding of dominant causal processes, as it is often used in contemporary ecology. However, a variety of empirical and statistical models are now commonly used in sediment studies. Prior to a survey of how sediment-studies have and can contribute to the evaluation of the role of com- plex mathematical models in environmental mon- itoring studies, some uses of models in palaeolim- nology are summarized. </p><p>2.1. Dating </p><p>Reliable dating of lake sediments is fundamen- tal to the success of palaeolimnology and it is in this area that the most widely used models (in palaeolimnology) are found. Recent (i.e. 100-150 years) sediments are generally dated using 2~pb (half-life 22.26 yr), except in relatively rare cases where annually-laminated sediments (varves) can be used (Renberg, 1981). 21pb is a natural ra- dioisotope derived from the decay of 226Ra. In lake sediments, 21pb is partitioned into a sup- ported (derived from in situ decay of 226Ra) and an unsupported component that is derived from atmospheric inputs via secondary decay from 226Rn (see Oldfield and Appleby, 1984, for de- tails). It is generally assumed that 226Ra and supported 21pb are in equilibrium, although this is not always the case (Battarbee, 1991). </p><p>Due to a variety of factors (e.g. non-uniform sediment accumulation rates and shifting foci of sediment deposition), deriving a chronology is not always a simple function of sediment depth and radioactive decay constants. For many small lakes with catchment disturbance (deforestation, ur- banisation, eutrophication), sediment loads to lakes have increased substantially over recent time-periods, with an associated increase in sedi- ment accumulation rates in the lake basin. These increased sediment accumulation rates result in non-linear relationships between 21pb concen- trations and depth. For these situations, an alter- native dating model is necessary - the constant rate of supply model (Appleby and Oldfield, </p><p>1978). Now widely used, it to may not be applica- ble in all lakes (e.g. sediment focusing) and other alternative models or combinations of models must be used to obtain a reasonable chronology (Oldfield and Appleby, 1984). In general, 2~Pb- dating works well but it is sometimes over-looked that the chronology is to some extent merely a function of the model chosen: independent checks on the derived-chronology are useful (Oldfield and Appleby, 1984). </p><p>For many small meso-eutrophic lakes with dis- turbed catchments, increased sediment accumula- tion rates pose a more substantial problem for dating than does sediment mixing. However, where benthic invertebrate populations are high or in shallow lakes with extensive wind-induced resuspension (Kristensen et al., 1992; Anderson and Odgaard, 1994), mixing can be problematical. So much so, that mixing parameters are built into dating models (Berner, 1980). When mixing is demonstrably high, and correctly dated, infer- ences of the onset of perturbation are required, e.g. for atmospheric contamination, deconvolu- tion techniques can be applied (Christensen and Osuna, 1989). In this approach, mixing functions are used to extract the original input signal from mixed, homogenous sediment profiles. Similarly, as a result of post-depositional diagenesis some chemical species are highly mobile within sedi- ments, e.g. sulphur, zinc. To overcome this prob- lem, Holdren et al. (1984) used a one-dimen- sional, diagcnetic equation to estimate the true onset of sulphur pollution as recorded in the sediments of a small lake in the Adirondack Mountains, New York State, by taking into ac- count post-depositional diffusion and mixing of sulphur. </p><p>2. 2. Transfer functions </p><p>Much of the relevance of palaeolimnology to studies of recent environmental change has de- rived from its ability to reconstruct water-chem- istry variables via microfossil transfer functions (e.g. pH, salinity, TP). Traditionally, fossil data have been interpreted in a subjective manner using assumptions about ecological tolerances of taxa and their environmental implications (Birks, </p></li><li><p>152 N.J. Anderson/Ecological Modelling 78 (1995) 149-172 </p><p>1992). In palaeolimnology, initial attempts to make interpretation more objective centred on the use of multivariate statistics to "classify" sedi- ment assemblages and later to relate them to dominant ecological variables. This approach (analogue matching sensu lato), exemplified - for diatoms - by a number of papers by Brugam (1980; Brugam et al., 1988), was largely derived from a similar approach used in palynology. </p><p>The recent development and application of transfer functions in palaeolimnology was largely associated with lake acidification and pH recon- structions (ter Braak and van Dam, 1989; Birks et al., 1990), primarily because of the well-known relationship between diatoms and pH (see Bat- tarbee, 1984, for a review). Transfer functions require an understanding of the present-day dis- tributions and ecological tolerances of the taxa being used, but as modern autecological data are usually lacking except for the most common of species, species-environmental relationships are usually defined by use of surface-sediment train- ing sets. In this approach, microfossil assemblages are enumerated for surface-sediment samples from lakes with modern water chemistry. Such a sampling strategy is inherent whatever statistical method is actually used to formulate the modern microfossil-water chemistry relationship (e.g. lin- ear regression, weighted averaging - see below). </p><p>Initial methods of reconstructing pH were largely variants on multiple-linear regression-type models, using either pH preference groups or individual taxa (Battarbee, 1984; Birks et al., 1990). It is now understood, however, that many taxa have non-linear responses to an environmen- tal variable over long gradients, ter Braak and Looman (1986) demonstrated how the response of a taxon to a given environmental variable can be described reasonably well by a Gaussian uni- modal response model. The relationship of indi- vidual taxa to the chosen environmental variable, can be fitted by maximum likelihood regression (ML; ter Braak and Looman, 1986; Birks et al., 1990) but this approach is computationally de- manding (Birks et al., 1990). A simpler approach but with similar ecological assumptions, is to use weighted averaging (WA) regression and calibra- tion (ter Braak and Barendregt, 1986). Birks et al. </p><p>(1990) demonstrated that WA methods provide similar predictive results (in terms of the stand- ard error of prediction) to ML Gaussian regres- sion and calibration. </p><p>Weighted averaging methods of regression and calibration were initially applied to lakewater pH (via both diatom and chrysophyte training sets) but since have been applied to a number of other parameters, including trace metals (Dixit et al., 1991), salinity (Fritz et al., 1991), dissolved or- ganic carbon (Kingston and Birks, 1990) and nu- trients (e.g. total phosphorus [TP], soluble reac- tive phosphorus, nitrogen; Hall and Smol, 1992; Anderson et al., 1993; Christie and Smol, 1993). Lake water temperature has also been inferred from chironomid head capsules (Walker et al., 1991). </p><p>Surface sediment samples provide a time-in- tegr...</p></li></ul>