Module 7 Ecosystems as Complex Systems

• Complex system


  A conglomeration that is greater than the sum of many heterogenous things taken together
• Ecological complexity


  An emerging multidisciplinary field of study that makes use of tools and concepts developed from the essential disciplines of complex systems science (CSS) namely physics, mathematics and computer science
• Ecological complexity


  • Characterized by local interactions between individual ecosystem components, feedbacks between processes occurring at different scales, amplification of minor variations in initial conditions, and the emergence of patterns in the absence of a global controller
• Ecological theory has provided the fundamental assumptions for figuring out possible solutions to major social, economic and environmental problems
• Complex problems that we experience today such as climate change, emerging and re-emerging diseases, inflation and wars can be regarded as neither social nor economic ones separately but as ones of the social social-economic-natural complex ecosystem
• Economic and natural systems possess different characteristics as indicated by their own structures, functions and developmental rules. However, their path to maturity are influenced by the structures and functions of the others
• Ecosystem


  • Predisposed to be involved in many different interactions that generate emergent properties -- patterns at higher levels emerge from localized interactions and selection processes acting at lower levels
  • Interactions between components is non-linear
  • Outcomes are determined by external conditions (i.e. the environment) and the extent by which ecosystem components organized themselves
• Complex systems


  • Brain
  • Global economy
• Phase transition


  A period of rapid change where non-linear systems may grow or decay at exponential rate
• Resiliency


  Achieved in the presence of alternative species
• Dimensions of complexity in ecology

  • Spatial
  • Temporal
  • Functional
• Spatial complexity


  • Species distribution
  • Vegetation patterns
• Spatial complexity measures


  • Bubble chart to profile population density and locations
  • Plotting presence of fruit bearing trees along elevation
  • Heatmap of plant species richness
• Temporal complexity


  • Changes in population
  • Effects of changes in climate and weather
  • Extinction
  • Invasion and successions
  • Predator-prey cycles
• Temporal Complexity: Perturbations affect ecosystem stability and complexity

  Resulting in unfavorable conditions
• Temporal complexity measures


  • Predator-prey density cycles
  • Biomass complexity decreasing over time due to soil contamination
• Such conditions can be analyzed by plotting pertinent measures of data whose patterns can be visualize in both the spatial and temporal dimensions (Spatio-Temporal). An example of this is shown in Figure 8 indicating changes in the biomass complexity of an ecosystem named "Makabuhay Forest".
• Structural


  Refers to relationships within the ecosystem as exemplified by food web and species interaction networks in Figure 9
• 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 (Minor & Urban, 2008).
• Time scales for movement of elements

  • Juvenile dispersal and recolonization of empty habitat patches (short time periods)
  • Migration and continuing metapopulations (intermediate time scales)
  • Species range expansion in response to natural forces such as climate change (largest time scales)
• Structural Complexity: Habitat connectivity


  Important for organisms to follow the range of environmental conditions they are used to, such as migrating towards the poles or high up in the mountains in response to global warming
• Fragmented habitats limit the gene pool for a particular species since the population is too isolated, more chances of inbreeding and disease are likely possible (Crain, 2015).
• Four kinds of connectivity networks or matrices

  • Planar
  • Random
  • Scale-free
  • Small-world
• Nodes represent an individual organism situated in a habitat patch while the edges represent the relations between two nodes. Hence, a graph or connectivity network is composed of a set of nodes and edges.
• Among the four kinds of networks, the more complex ideal habitat network may resemble a scale-free network with several large hubs connected to multiple smaller patches.
• Structural Complexity: Highly clustered nodes


  Facilitate: (1) spread of disturbances and (2) dispersal that aids recovery from an environmental disturbance. Also, may be more resilient to patch removal.
• High compartmentalization


  Slows movement through a network and may isolate the potentially cascading effects of disturbance.
• Scale-free networks are highly resistant to random disturbances but vulnerable to deliberate attacks on the hubs.
• The rampant use of pesticides and the occurrence of heavy industrialization in GRA resulted in the destruction of high-degree nodes as indicated by low species count. As a consequence this led to the promotion of contaminated waterways and rivers. The introduction of invasive species in the river brought the loss of beneficial species. The reduced complexity of this ecosystem impacted on the overall economy and health of local communities as indicated by loss of both main and alternative native species; high food prices and malnutrition; diarrhea and infectious diseases and decline in provisioning services.
• Ecosystem is a network of many components whose aggregate behavior is both due to, and gives rise to, multiple-scale structural and dynamical patterns which are not inferable from a system description that spans only a narrow window of resolution (Complex Environmental Systems Lab, 2014 and Parrott & Kok, 2000).
• Research findings validated that common characteristic patterns of temporal, spatial, spatio-temporal and structural signatures are shared across all types of complex systems (Parott, 2010)
• 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
• Regularity versus complexity

  Both highly ordered and highly disordered (random) systems are simple systems and mostly complex systems are found in the intermediate zone of regularity (Parrot, 2010)
• Properties of a complex system

  Found "at the edge of chaos" (Langton, 1992 and Parrot, 2010) in the middle of two extremes of order (uniform spatial pattern or temporal equilibrium) and disorder (random spatial distribution or white noise), demonstrating equal distribution between underlying regularity and complete unpredictability (chaos)
• An ecosystem tends towards greater complexity via the process of self-organization, which draws the system away from the two extremes of order and disorder to a state of maximal complexity
• This state of maximal complexity is a site-specific attractor which is constrained by prevailing physical and environmental conditions -- natural disturbance events may cause an ecosystems state to tend towards greater disorder, whereas human intervention in the form of energy input can move the system state towards greater order than might be attainable naturally
• Ordered ecosystem


  • Agricultural monoculture, such as a cornfield planted in rows
• Disordered ecosystem


  • Recently opened gap in a forest, in which seeds have randomly fallen and just begun to germinate
• Complex ecosystem


  • Undisturbed, ancient tropical rainforest
• Temporal, spatial and structural data would provide information that would help orient your point of view on how to preserve or relieve an ecosystem of pressures depending on the case at hand