M7: ecosystems as complex systems

• Community

  • Assemblage of populations that occupy a given area, interacting either directly or indirectly
  • Collection of species that share the same environment
  • Can be of any size
  • Focuses on the interactions among different species
• Ecosystem

  • Unit including all the organisms interacting with each other (biotic community) in a given area interacting with the physical environment
  • First unit in the ecological hierarchy that is complete
• Energy from sunlight

  • driving force of an ecosystem
  • Light and heat form
• Ecological complexity

  • differs from other analytical approaches in that it is based upon a conceptual model in which entities exist in a hierarchy of interrelated organizational levels
  • “The whole is more than the sum of the parts”
• Parts of Complex Theory

  1. Local interactions

  • Situated at the base

  1. Feedback

  • Feedbacks occurring between different scales
  • Higher levels can interact w lower levels via feedback loops

  1. Emergence of patterns 
• For ecosystems…

  • Local interactions would be among different populations which form a higher level
  • The (emergent) higher level entity would be the community. Interactions among communities form a global level community
  • The global level community would be the ecosystem
• Ecological theory has provided the fundamental assumptions for figuring out possible solutions to major social, economic and environmental problems that come into view indistinctly. 
• Complexity

  • primary product of four primary parameters
• 4 primary parameters

  1. Number of elements
  2. Nonlinearity
  3. Connectivity
  4. Autonomy and Adaption
• Number of elements

  • Initial definition
  • #  of elements at different hierarchy within a living system
• Nonlinearity

  • Non-additive interactions and feedback loops over time can give exponential relations between the input and output to systems and lead to phase transition (i.e. a period of rapid change where non-linear systems may grow or decay at exponential rate)
  • Complex systems are able to shift or flip into whole new regimes within very brief periods of time. Some small change to the input value may trigger a large systemic effect (sensitivity to initial conditions).
• Connectivity

  • often appear as networks in a higher level that indicates the degree of how things flow in the network. 
  • Resiliency is achieved in the presence of alternative species
• Autonomy and Adaptation

  • enables self-organization and the process of evolution that shapes complex systems on macro scale. -
  • Typical examples of complex systems include: ecosystems, economies, transportation networks and neural systems (i.e. brain).
• Measures of Complexity in an ecosystem

  1. Spatial
  2. Temporal
  3. Structural
• Spatial

  • the manner species are organized in a given geographical location
  • Ex: species distribution and vegetation patterns
• Temporal

  • Its measure characterizes time series of different variables describing the dynamics of a system 
  • It can be derived from dynamics or changes in population, effects of changes in climate and weather, extinction, invasion and successions and predator-prey cycles
• Structural

  • relationships within the ecosystem
  • Analyzing connectivity of habitat patches is highly relevant in understanding the movement of elements (i.e. genes, individuals, populations, and species) on different time scales
  • (1) Juvenile dispersal and recolonization of empty habitat patches as influenced by connectivity are usually observed in short time periods; (2) migration and continuing metapopulations are recorded at intermediate time scales; (3) species range expansion in response to natural forces such as climate change are observed in largest time scales
• 4 kinds of connectivity networks

  1. Planar
  2. Random
  3. Scale-free
  4. Small-world
• Types of ecosystems

  1. Terrestrial Ecosystems: (a) deserts, (b) savannahs, (c) steppe, (d) temperate forest, (e) tropical forest, (d) boreal forest (taiga), (e) tundra and (d) Mediterranean vegetation.
  2. Water Ecosystems: (a) freshwater ecosystems (lakes and ponds, rivers and torrents, marshes and swamps) and (b) marine ecosystems (reef, oceans, continental plateaus, nutrient upstream-flowing areas and estuaries). 
  3. Artificial ecosystems: (a) urban-industrial ecosystems (metropolises), (b) rural ecosystems (small towns) and (c) agro-ecosystems (farmlands).
• 2 types of measures of complexity 

  • Type 1 measures increase with increasing disorder in the system in a linear manner
  • Type 2 measures are those of a convex function that assign their highest scores to systems whose regularity lies at the intermediate level. The endpoint is to differentiate between simple systems versus those that are complex regardless of what type of measure is used 
• Complexity refers to systems with many parts that organize themselves to become more ordered and informed. These systems are highly interconnected and interactive. Emergence, or new properties, arises from this self-organization process.