Many different models are used to study ecosystem dynamics, including holistic, experimental, conceptual, analytical, and simulation models.
Differentiate between conceptual, analytical, and simulation models of ecosystem dynamics, and mesocosm and microcosm research studies
- A holistic ecosystem model quantifies the dynamics of an entire ecosystem.
- Scientists can use experimental systems, such as a microcosms or mesocosms, to study ecosystems under controlled laboratory conditions.
- A conceptual model uses flow charts to show the interactions between living and nonliving components of the ecosystem.
- An analytical model uses simple mathematical formulas to predict the effects of environmental disturbances on an ecosystem’s structure and dynamics.
- A simulation model predicts the effects of environmental disturbances using complex computer algorithms; they are usually fairly-reliable predictors.
- mesocosm: a small portion of the natural environment that is brought under controlled conditions for experimental purposes
- microcosm: an artificial, simplified ecosystem that is used to simulate and predict the behaviour of natural ecosystems under controlled conditions
Research into Ecosystem Dynamics: Ecosystem Experimentation and Modeling
Ecosystem dynamics is the study of the changes in ecosystem structure caused by environmental disturbances or by internal forces. Various research methodologies measure ecosystem dynamics. Some ecologists study ecosystems using controlled experimental systems, while some study entire ecosystems in their natural state; others use both approaches.
Holistic Ecosystem Model
A holistic ecosystem model attempts to quantify the composition, interaction, and dynamics of entire ecosystems. A food web is an example of a holistic ecosystem model, which is the most representative of the ecosystem in its natural state. However, this type of study is limited by time and expense, as well as its limited feasibility to conduct experiments on large natural ecosystems.
For these reasons, scientists study ecosystems under more controlled conditions. Experimental systems usually involve either partitioning a part of a natural ecosystem that can be used for experiments, termed a mesocosm, or by re-creating an ecosystem entirely in an indoor or outdoor laboratory environment, which is referred to as a microcosm. A major limitation to these approaches is that removing individual organisms from their natural ecosystem or altering a natural ecosystem through partitioning may change the dynamics of the ecosystem. These changes are often due to differences in species numbers and diversity, but also to environment alterations caused by partitioning (mesocosm) or re-creating (microcosm) the natural habitat. Thus, these types of experiments are not totally predictive of changes that would occur in the ecosystem from which they were gathered.
Mesocosm: Greenhouses contribute to mesocosm studies because they allow us to control the environment and, thus, the experiment. The mesocosms in this example, tomato plants, have been placed in a greenhouse to control the air, temperature, water, and light distribution in order to observe the effects when exposed to different amounts of each factor.
As both of these approaches have their limitations, some ecologists suggest that results from these experimental systems should be used only in conjunction with holistic ecosystem studies to obtain the most representative data about ecosystem structure, function, and dynamics.
Scientists use the data generated by these experimental studies to develop ecosystem models that demonstrate the structure and dynamics of ecosystems. Three basic types of ecosystem modeling are routinely used in research and ecosystem management: conceptual models, analytical models, and simulation models.
A conceptual model consists of flow charts to show interactions of different compartments of the living and nonliving components of the ecosystem. A conceptual model describes ecosystem structure and dynamics and shows how environmental disturbances affect the ecosystem, although its ability to predict the effects of these disturbances is limited.
Analytical and simulation models are mathematical methods of describing ecosystems that are capable of predicting the effects of potential environmental changes without direct experimentation, although with limitations in accuracy. An analytical model is created using simple mathematical formulas to predict the effects of environmental disturbances on ecosystem structure and dynamics.
A simulation model is created using complex computer algorithms to holistically model ecosystems and to predict the effects of environmental disturbances on ecosystem structure and dynamics. Ideally, these models are accurate enough to determine which components of the ecosystem are particularly sensitive to disturbances. They can serve as a guide to ecosystem managers (such as conservation ecologists or fisheries biologists) in the practical maintenance of ecosystem health.