Mooij W.M.,Netherlands Institute of Ecology |
Mooij W.M.,Wageningen University |
Brederveld R.J.,WitteveenBos |
de Klein J.J.M.,Wageningen University |
And 26 more authors.
Environmental Modelling and Software | Year: 2014
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. © 2014 The Authors.
Teal L.R.,University of Aberdeen |
Teal L.R.,Institute for Marine Resource and Ecosystem Studies IMARES |
Parker E.R.,CEFAS - Center for Environment, Fisheries and Aquaculture Science |
SOlan M.,University of Aberdeen
Marine Ecology Progress Series | Year: 2010
Faunal mediated particle and porewater mixing (bioturbation) alters the structure ofthe surface sediment layer, forming a distinct mixed layer, where the majority of organicmatter degradation takes place. Current methods of assessing benthic habitat quality often reference this mixed layer as an indicator of benthic activity. Whilst a great deal of effort has been devoted to linking macro-invertebrate activity to the mixing depth, less attention has been given to defining what the mixing depth represents in terms of ecosystem process and function. Here, in situ sediment profile images are analysed using grey scale intensity analysis to distinguish the mixed zone and relate it to the physicochemicalenvironment in order to determine the biological, chemical and physical variables most influential in its formation. Significant differences were found between biogeochemical conditions within the mixed layer relative to the underlying historic sediment layer. These were attributed to a combination of environmental variables (Fe, Mn, Si, chlorophyll a and NO3 -) rather than a single dominant driver of change. Although these findings are consistent across multiple locations, the driver(s) that influence the depth of the mixed layer are site- and season-specific. The mixing depth thus provides a reasonable approximation of benthic ecosystem functioning, but when considering ecosystem process the link between the mixing depth and its driving factors (faunal mixing, food input, environmental conditions) is highly context-dependent. Conclusions on benthic community dynamics and ecosystem process, including assessments of habitat quality, cannot therefore be drawn from estimates of the mixing depth alone. © Inter-Research 2010.