Andrea S. Downing

Challenges and Opportunities for Integrating Lake Ecosystem Modelling Approaches

A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others (‘reinventing the wheel’). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available (‘having tunnel vision’). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and trait-based models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its ‘leading principle’, there are many opportunities for combining approaches. We take the point of view that a single ‘right’ approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models.

A community-based framework for aquatic ecosystem models

Here, we communicate a point of departure in the development of aquatic ecosystem models, namely a new community-based framework, which supports an enhanced and transparent union between the collective expertise that exists in the communities of traditional ecologists and model developers. Through a literature survey, we document the growing importance of numerical aquatic ecosystem models while also noting the difficulties, up until now, of the aquatic scientific community to make significant advances in these models during the past two decades. Through a common forum for aquatic ecosystem modellers we aim to (i) advance collaboration within the aquatic ecosystem modelling community, (ii) enable increased use of models for research, policy and ecosystem-based management, (iii) facilitate a collective framework using common (standardised) code to ensure that model development is incremental, (iv) increase the transparency of model structure, assumptions and techniques, (v) achieve a greater understanding of aquatic ecosystem functioning, (vi) increase the reliability of predictions by aquatic ecosystem models, (vii) stimulate model inter-comparisons including differing model approaches, and (viii) avoid ‘re-inventing the wheel’, thus accelerating improvements to aquatic ecosystem models. We intend to achieve this as a community that fosters interactions amongst ecologists and model developers. Further, we outline scientific topics recently articulated by the scientific community, which lend themselves well to being addressed by integrative modelling approaches and serve to motivate the progress and implementation of an open source model framework.

The resilience and resistance of an ecosystem to a collapse of diversity.

Diversity is expected to increase the resilience of ecosystems. Nevertheless, highly diverse ecosystems have collapsed, as did Lake Victoria’s ecosystem of cichlids or Caribbean coral reefs. We try to gain insight to this paradox, by analyzing a simple model of a diverse community where each competing species inflicts a small mortality pressure on an introduced predator. High diversity strengthens this feedback and prevents invasion of the introduced predator. After a gradual loss of native species, the introduced predator can escape control and the system collapses into a contrasting, invaded, low-diversity state. Importantly, we find that a diverse system that has high complementarity gains in resilience, whereas a diverse system with high functional redundancy gains in resistance. Loss of resilience can display early-warning signals of a collapse, but loss of resistance not. Our results emphasize the need for multiple approaches to studying the functioning of ecosystems, as managing an ecosystem requires understanding not only the threats it is vulnerable to but also pressures it appears resistant to.

Serving many at once

Simulation modelling in ecology is a field that is becoming increasingly compartmentalized. Here we propose a Database Approach To Modelling (DATM) to create unity in dynamical ecosystem modelling with differential equations. In this approach the storage of ecological knowledge is independent of the language and platform in which the model will be run. To create an instance of the model, the information in the database is translated and augmented with the language and platform specifics. This process is automated so that a new instance can be created each time the database is updated. We describe the approach using the simple Lotka-Volterra model and the complex ecosystem model for shallow lakes PCLake, which we automatically implement in the frameworks OSIRIS, GRIND for MATLAB, ACSL, R, DUFLOW and DELWAQ. A clear advantage of working in a database is the overview it provides. The simplicity of the approach only adds to its elegance. Scientific and educational experience with the proposed Database Approach To Modelling (DATM) shows the following:It facilitated overview of and insight in the model by developers and users.Allowed for a much more dynamic scientific development of the model.Allowed for a direct implementation of these developments in multiple platforms.

Zooming in on size distribution patterns underlying species coexistence in Baltic Sea phytoplankton.

Scale is a key to determining which processes drive community structure. We analyse size distributions of phytoplankton to determine time scales at which we can observe either fixed environmental characteristics underlying communities structure or competition-driven size distributions. Using multiple statistical tests, we characterise size distributions of phytoplankton from 20-year time series in two sites of the Baltic Sea. At large temporal scales (5-20 years), size distributions are unimodal, indicating that fundamental barriers to existence are here subtler than in other systems. Frequency distributions of the average size of the species weighted by biovolume are multimodal over large time scales, although this is the product of often unimodal short-term (<1 year) patterns. Our study represents a much-needed structured, high-resolution analysis of phytoplankton size distributions, revealing that short-term analyses are necessary to determine if, and how, competition shapes them. Our results provide a stepping-stone on which to further investigate the intricacies of competition and coexistence.

Was Lates Late? : A Null Model for the Nile Perch Boom in Lake Victoria

Nile perch (Lates niloticus) suddenly invaded Lake Victoria between 1979 and 1987, 25 years after its introduction in the Ugandan side of the lake. Nile perch then replaced the native fish diversity and irreversibly altered the ecosystem and its role to lakeshore societies: it is now a prised export product that supports millions of livelihoods. The delay in the Nile perch boom led to a hunt for triggers of the sudden boom and generated several hypotheses regarding its growth at low abundances – all hypotheses having important implications for the management of Nile perch stocks. We use logistic growth as a parsimonious null model to predict when the Nile perch invasion should have been expected, given its growth rate, initial stock size and introduction year. We find the first exponential growth phase can explain the timing of the perch boom at the scale of Lake Victoria, suggesting that complex mechanisms are not necessary to explain the Nile perch invasion or its timing. However, the boom started in Kenya before Uganda, indicating perhaps that Allee effects act at smaller scales than that of the whole Lake. The Nile perch invasion of other lakes indicates that habitat differences may also have an effect on invasion success. Our results suggest there is probably no single management strategy applicable to the whole lake that would lead to both efficient and sustainable exploitation of its resources.

Assembling the pieces of Lake Victoria's many food webs: Reply to Kolding

Stockholm University, Department of Systems Ecology, SE-10691, Stockholm, Sweden Aquatic Ecology and Water Quality Management Group, Department of Environmental Sciences, Wageningen University, P.O. Box 47, NL-6700 AA Wageningen, Netherlands Netherlands Environmental Assessment Agency, P.O. Box 303, 3720 AH Bilthoven, Netherlands Institute of Biology, Leiden University, Sylviusweg 72, 2300 RA Leiden, Netherlands Aquaculture and Fisheries Group, Department of Animal Sciences, Wageningen University, P.O. Box 338, 6700 AH Wageningen, Netherlands Department of Aquatic Ecology, Netherlands Institute of Ecology, P.O. Box 50, NL-6700 AB, Wageningen, Netherlands