Biodiversity and ecosystem functioning: A complex adaptive systems approach

Norberg, Jon

Limnol. Oceanogr., 49(4_part_2), 2004, 1269-1277 | DOI: 10.4319/lo.2004.49.4_part_2.1269

ABSTRACT: Environmental factors regulate biodiversity through species sorting processes. Species distributions in communities affect ecosystem processes and environmental factors. These dynamics are determined by the properties (traits) of species in the community. The optimal temperatures for growth, the minimal amount of resource that sustains positive mass balance, and the amount of energy allocated to predator defenses are examples of such traits. Over time, the trait distributions in communities may change in response to environmental changes, which, in turn, changes the processes and consequently the structure of the system. The result of such processes is the focus of complex adaptive systems (CAS) theory. This paper gives an overview of how CAS theory can contribute to understanding the role of biodiversity on the ability of functional groups that make up the ecosystem to change their species compositions in response to changes in the environment. Any trait that requires investment of energy, mass, or time is subjected to a tradeoff for alternative use of this resource. Such interspecies tradeoff relationships can be used to make predictions about past environmental conditions, as well as the response of the properties of a group of species, e.g., total productivity and species distributions, to future changes in the environment. The trait based framework presented here makes explicit predictions regarding the relation between the environment, trait distributions, and ecosystem processes. Trait variance, a measure of the width of the distribution of traits in the community, is proportional to the rate at which species within functional groups can replace each other in response to environmental changes. This adaptive capacity is crucial for the ecosystem’s ability to maintain certain processes under times of change. Examples of empirical tradeoffs are given as well as how to formalize them to use in the CAS framework.

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