SlideShare a Scribd company logo
Laws, Theories, and Patterns in Ecology:
Variability & Organisms
Seminar in Ecology
10/31
All organisms are unique
• No two organisms or species are identical because of genetic variability and environmental heterogeneity
(differences in climate and distribution of resources over space and time)
• Organisms with sexual reproduction display more variability and diversity, however even clonally reproducing
species display differences in genomes.
• Ex. H.pylori genomic mapping by gel electrophoresis showed considerable variation in the size of genome and
location of rRNA strains ( Tayloer et al. 1992)
Burns et al. 2004 Silva et al. 2011– Anuran diversity
All organisms are unique
• Multicellular organisms are more diverse than bacteria.
• Variation sets biology apart from other sciences, other sciences have more narrow considerations of
organization
• All molecules are made with the same chemical composition, and electrons remain electrons in whatever
system they are studied.
• Variation in organisms and environmental heterogeneity constrains ecological predictions, especially in
population modeling.
• Ex. Metapopulation Model
• Equal chances of colonization in each patch
• Equal chances of extinction in each patch
• Ex. Exponential Model
• No emigration or immigration
• No genetic variation
• Equal birth and death rates
Population, resource, and habitat heterogeneity
• Differences in the distribution of populations and resources over space and time are due to abiotic and biotic
factors
• Abiotic mechanisms: Density-independent factors such as geological, climatic, and hydrologic variation (
precipitation, temperature, soil moisture, disturbances)
• Biotic mechanism- Density- dependent factors such as competition for limited resources, predator-prey
dynamics, disease and parasite prevalence
• Habitat heterogeneity is a major structural force in ecological communities.
• Habitats with higher heterogeneity support higher levels of species diversity ( Pianka 1966)
• At the global scale, habitat turnover creates opportunity for genetic isolation leading to speciation
• At local scales, variation in factors such as precipitation, temperature, wave exposure, and topography
provide more available niches and promotes species coexistence
Briefly,metapopulation dynamics
• Developed by Levins (1969) to describe rate of change in habitat patches
• metapopulation- “population of populations” in which subpopulations occupy spatially distinct habitat patches.
• Suitable patches occur within a matrix of unsuitable patches
• Metapopulations are maintained by the movement of subpopulations between suitable patches via dispersal,
and the key processes of extinction and recolonization
Dp/dt= mp(1-p)-cp  rate of change
p- proportion of occupied patches
m- rate of movement between patches
c- extinction rate
Ji=Ci/Ci + Exi-Probablity of patch occupancy given a stochastic-steady state
Ci=probability of recolonization of each patch I
Exi= probability of extinction within each patch
Metapopulation uses
• Can provide important information to the conservation of wildlife populations
• Most wildlife habitats display a degree of patchiness due to differences in habitat size, isolation, and edge
characteristics
• Animal movement between patches depend on these landscape factors.
• Understanding how change in landscape and habitat factors affect the dispersal of wildlife are important and can
give information on population dynamics and conservation strategies
• Metapopulations also provide insight on source-since dynamics and the concept of habitat corridors.
• Source- at low density and no immigration, positive growth rate
• Sink- at low density and immigration, negative growth rate
• Habitat corridor- linear habitats within a dissimilar matrix which connect two larger habitats (Beier and Noss 1998)
Limitations of metapopulation models
• limited to one species
• dealing with probabilities
• Difficult to account for spatial differences in habitat quality such as habitat fragmentation and destruction due to
human activities.
• Can’t account for habitat destruction where patch recolonization does occur immediately
• Colonization and extinction are independent, however they likely show some connectivity.
• Habitat corridors may provide increased colonization and immigration, but may also increase rates of
disease and pathogens.
• Unclear how temporal variability such as primary production of plants effects spatially structured populations
Scaling
• The form and function of organisms is very diverse and covers a large scale from the largest animals to the smallest
units of life.
• Empirically, organisms range from 1um to 100 m in size and generation times range from hours to centuries.
• Lower limits of size can be explained by the housing of biomolecular machinery that allow cells to function, while upper
limits are less clear
• The use of power functions ( y=aXb) help describe scaling relationships.
• Ex- Metabolic rate= a * massb , where “a” is the conversion factor and “b” is the power function
• When b=1, isometric relationship, relationship is constant
• When b ≠1, allometric relationship, relationship changes with mass ( 0<b<1)
(http://mathbench.umd.edu/modules/misc_scaling/page06.htm)
Scaling: Allometric laws
• Most power functions when applied to living systems show allometric scaling
• Allometric laws are based on empirical observations
• Laws help answer questions pertaining to form (surface area and volume, size and strength) and physiological
function ( metabolic rate and size, heart rate and size)
• Kleiber’s law – metabolic rate (R) is equal to ¾ power of mass
• Law applicable from smallest to largest organisms
• Also, the ¼ power law can be applied life-span( ~.15-.30, Speakman 2005), where bigger animals with slower
metabolism live longer
Scaling: Metabolic Theory of Ecology
• MTE is an extension of Kleiber’s law which proposes that the metabolic rate of organisms controls
ecological processes at all levels of organization ( Brown et al., 2004)
• Metabolic rates effect resource uptake from the environment and resource allocation for
reproduction, growth, survival
• Metabolic rates can influence processes such as life-history traits, population growth rates, and
ecosystem processes such as biomass production
• Theory takes into account the variables: metabolic rate, temperature, and resource availability.
• Ex. One part of MTE states that sp. diversity decreases linearly with inverse temperature
Discussion
Tetragnatha versicolor
S. Fork Eel River, 3 sites in viewFeeding experiment
enclosures
Emerging mayflies
Photo credit: Hiromi Uno, 2014
Trapped mayflies in T.versicolor web
Variability and Organisms
Variability and Organisms
Variability and Organisms

More Related Content

PPTX
Chapters 8 11 ecology
PPT
Grade 10 - Population Ecology
PPTX
Principle Ecology
PPTX
Allee effect
PPT
Wikibio100 2
DOCX
Limiting factors
PPTX
Laws of limiting factors
PPTX
Law of limiting factors
Chapters 8 11 ecology
Grade 10 - Population Ecology
Principle Ecology
Allee effect
Wikibio100 2
Limiting factors
Laws of limiting factors
Law of limiting factors

What's hot (20)

PPTX
Limiting factors
PPTX
Population and Community
PDF
Seminário 3 cottenie_et_al-2003_zooplankton (1)
PDF
Seminário 5 mc_cauley 2007_dragonfly (2)
PDF
Seminário 2 capers_et_al-2010_aquatic plant (2)
PPT
Ecological sampling
PDF
Is homo sapiens a key species in an ecological system?
DOC
Allometry
PPTX
Chapters 21 23 ecology
PPTX
Ecology Notes
PPT
Population Ecology
PPTX
R AND K SELECTED SPECIES powerpoint presentation
PPT
Principles Of Ecology2007
PDF
Limiting factors
PPT
Populations
PPTX
Populations Communities And Ecosystems
PPTX
Population: Carrying Capacity and Limiting Factors in Natural systems
PDF
PPT
r and k selection
PPTX
Biology 205 12
Limiting factors
Population and Community
Seminário 3 cottenie_et_al-2003_zooplankton (1)
Seminário 5 mc_cauley 2007_dragonfly (2)
Seminário 2 capers_et_al-2010_aquatic plant (2)
Ecological sampling
Is homo sapiens a key species in an ecological system?
Allometry
Chapters 21 23 ecology
Ecology Notes
Population Ecology
R AND K SELECTED SPECIES powerpoint presentation
Principles Of Ecology2007
Limiting factors
Populations
Populations Communities And Ecosystems
Population: Carrying Capacity and Limiting Factors in Natural systems
r and k selection
Biology 205 12
Ad

Viewers also liked (20)

PPTX
Estudiante
PPTX
Presentation1
PPT
Introduction to Information Ecology: Journey from Rio to Johannesburg & beyond
PPTX
Historical Aspects of ECOLOGY
PPTX
Environmental Laws
PPTX
Biogeochemical cycles and conservation ecology 2010 edition
PDF
Environmental laws – the indian scenario
ODP
Environmental laws in india
PPTX
Environmental laws and regulations – indian scenario
PPT
Basic laws on environmental protection
PPT
Ecology & environmental degradation final
PPTX
environmental laws
PPT
laws of environmental protection - India
PDF
Ecology
PPTX
Biogeochemical Cycle, Pollution, and Recycling of Organic Waste ppt
PPTX
Ecology ppt
DOCX
Ecology
PPT
Biodiversity and Human Population Growth
PDF
Environmental Laws
PPT
Threats to Biodiversity
Estudiante
Presentation1
Introduction to Information Ecology: Journey from Rio to Johannesburg & beyond
Historical Aspects of ECOLOGY
Environmental Laws
Biogeochemical cycles and conservation ecology 2010 edition
Environmental laws – the indian scenario
Environmental laws in india
Environmental laws and regulations – indian scenario
Basic laws on environmental protection
Ecology & environmental degradation final
environmental laws
laws of environmental protection - India
Ecology
Biogeochemical Cycle, Pollution, and Recycling of Organic Waste ppt
Ecology ppt
Ecology
Biodiversity and Human Population Growth
Environmental Laws
Threats to Biodiversity
Ad

Similar to Variability and Organisms (20)

PPT
Lecture 1 introduction & populations
PPTX
Ecology
PPTX
Ecology 407 Organism and their Interaction with their environment
PPTX
ecology edit EPI.pptx transmission pathway
PPTX
ecology_part[1].pptx, biome educational purpose
PPT
Ecology definition &amp; scope
PPTX
Evolution and Coevolution.pptx
PPTX
BSBT lecture 1.pptx
PPTX
Application of ecological principles in restoration of degraded habitats
PPTX
PPTX
Ecosystem and Ecology.PPtx
PDF
Life Sciences Gade 11 Term 3 Week 7_2020 (1).pdf
PPTX
Basics of Biodiversity
PPTX
Population dynamics
PPTX
UNIT 1.pptx
PPTX
population, community and food web.pptx
PPT
L1 ap 2014 defining bio
PDF
dr. regunay enr
PPT
Principles of ecology
PPTX
Unit 3_Population Ecology_Complete.pptx
Lecture 1 introduction & populations
Ecology
Ecology 407 Organism and their Interaction with their environment
ecology edit EPI.pptx transmission pathway
ecology_part[1].pptx, biome educational purpose
Ecology definition &amp; scope
Evolution and Coevolution.pptx
BSBT lecture 1.pptx
Application of ecological principles in restoration of degraded habitats
Ecosystem and Ecology.PPtx
Life Sciences Gade 11 Term 3 Week 7_2020 (1).pdf
Basics of Biodiversity
Population dynamics
UNIT 1.pptx
population, community and food web.pptx
L1 ap 2014 defining bio
dr. regunay enr
Principles of ecology
Unit 3_Population Ecology_Complete.pptx

More from Robin Shin (7)

PPTX
Advancement2 2
PPTX
Otolith2
PPTX
Robinshin
PPTX
Robinshin
PPTX
Presentation1
PPTX
Seminar eco 2015
PPTX
History of the pacific sardine fishery and its
Advancement2 2
Otolith2
Robinshin
Robinshin
Presentation1
Seminar eco 2015
History of the pacific sardine fishery and its

Recently uploaded (20)

PPT
6.1 High Risk New Born. Padetric health ppt
PPTX
ECG_Course_Presentation د.محمد صقران ppt
PPTX
neck nodes and dissection types and lymph nodes levels
PPTX
Application of enzymes in medicine (2).pptx
PPTX
C1 cut-Methane and it's Derivatives.pptx
PPTX
Science Quipper for lesson in grade 8 Matatag Curriculum
PPTX
Overview of calcium in human muscles.pptx
PDF
Warm, water-depleted rocky exoplanets with surfaceionic liquids: A proposed c...
PPTX
2. Earth - The Living Planet Module 2ELS
PDF
Assessment of environmental effects of quarrying in Kitengela subcountyof Kaj...
PPTX
POULTRY PRODUCTION AND MANAGEMENTNNN.pptx
PDF
The scientific heritage No 166 (166) (2025)
PDF
Cosmic Outliers: Low-spin Halos Explain the Abundance, Compactness, and Redsh...
PDF
Formation of Supersonic Turbulence in the Primordial Star-forming Cloud
PPTX
TOTAL hIP ARTHROPLASTY Presentation.pptx
PPTX
7. General Toxicologyfor clinical phrmacy.pptx
PDF
Biophysics 2.pdffffffffffffffffffffffffff
PDF
SEHH2274 Organic Chemistry Notes 1 Structure and Bonding.pdf
DOCX
Q1_LE_Mathematics 8_Lesson 5_Week 5.docx
PDF
Placing the Near-Earth Object Impact Probability in Context
6.1 High Risk New Born. Padetric health ppt
ECG_Course_Presentation د.محمد صقران ppt
neck nodes and dissection types and lymph nodes levels
Application of enzymes in medicine (2).pptx
C1 cut-Methane and it's Derivatives.pptx
Science Quipper for lesson in grade 8 Matatag Curriculum
Overview of calcium in human muscles.pptx
Warm, water-depleted rocky exoplanets with surfaceionic liquids: A proposed c...
2. Earth - The Living Planet Module 2ELS
Assessment of environmental effects of quarrying in Kitengela subcountyof Kaj...
POULTRY PRODUCTION AND MANAGEMENTNNN.pptx
The scientific heritage No 166 (166) (2025)
Cosmic Outliers: Low-spin Halos Explain the Abundance, Compactness, and Redsh...
Formation of Supersonic Turbulence in the Primordial Star-forming Cloud
TOTAL hIP ARTHROPLASTY Presentation.pptx
7. General Toxicologyfor clinical phrmacy.pptx
Biophysics 2.pdffffffffffffffffffffffffff
SEHH2274 Organic Chemistry Notes 1 Structure and Bonding.pdf
Q1_LE_Mathematics 8_Lesson 5_Week 5.docx
Placing the Near-Earth Object Impact Probability in Context

Variability and Organisms

  • 1. Laws, Theories, and Patterns in Ecology: Variability & Organisms Seminar in Ecology 10/31
  • 2. All organisms are unique • No two organisms or species are identical because of genetic variability and environmental heterogeneity (differences in climate and distribution of resources over space and time) • Organisms with sexual reproduction display more variability and diversity, however even clonally reproducing species display differences in genomes. • Ex. H.pylori genomic mapping by gel electrophoresis showed considerable variation in the size of genome and location of rRNA strains ( Tayloer et al. 1992) Burns et al. 2004 Silva et al. 2011– Anuran diversity
  • 3. All organisms are unique • Multicellular organisms are more diverse than bacteria. • Variation sets biology apart from other sciences, other sciences have more narrow considerations of organization • All molecules are made with the same chemical composition, and electrons remain electrons in whatever system they are studied. • Variation in organisms and environmental heterogeneity constrains ecological predictions, especially in population modeling. • Ex. Metapopulation Model • Equal chances of colonization in each patch • Equal chances of extinction in each patch • Ex. Exponential Model • No emigration or immigration • No genetic variation • Equal birth and death rates
  • 4. Population, resource, and habitat heterogeneity • Differences in the distribution of populations and resources over space and time are due to abiotic and biotic factors • Abiotic mechanisms: Density-independent factors such as geological, climatic, and hydrologic variation ( precipitation, temperature, soil moisture, disturbances) • Biotic mechanism- Density- dependent factors such as competition for limited resources, predator-prey dynamics, disease and parasite prevalence • Habitat heterogeneity is a major structural force in ecological communities. • Habitats with higher heterogeneity support higher levels of species diversity ( Pianka 1966) • At the global scale, habitat turnover creates opportunity for genetic isolation leading to speciation • At local scales, variation in factors such as precipitation, temperature, wave exposure, and topography provide more available niches and promotes species coexistence
  • 5. Briefly,metapopulation dynamics • Developed by Levins (1969) to describe rate of change in habitat patches • metapopulation- “population of populations” in which subpopulations occupy spatially distinct habitat patches. • Suitable patches occur within a matrix of unsuitable patches • Metapopulations are maintained by the movement of subpopulations between suitable patches via dispersal, and the key processes of extinction and recolonization Dp/dt= mp(1-p)-cp  rate of change p- proportion of occupied patches m- rate of movement between patches c- extinction rate Ji=Ci/Ci + Exi-Probablity of patch occupancy given a stochastic-steady state Ci=probability of recolonization of each patch I Exi= probability of extinction within each patch
  • 6. Metapopulation uses • Can provide important information to the conservation of wildlife populations • Most wildlife habitats display a degree of patchiness due to differences in habitat size, isolation, and edge characteristics • Animal movement between patches depend on these landscape factors. • Understanding how change in landscape and habitat factors affect the dispersal of wildlife are important and can give information on population dynamics and conservation strategies • Metapopulations also provide insight on source-since dynamics and the concept of habitat corridors. • Source- at low density and no immigration, positive growth rate • Sink- at low density and immigration, negative growth rate • Habitat corridor- linear habitats within a dissimilar matrix which connect two larger habitats (Beier and Noss 1998)
  • 7. Limitations of metapopulation models • limited to one species • dealing with probabilities • Difficult to account for spatial differences in habitat quality such as habitat fragmentation and destruction due to human activities. • Can’t account for habitat destruction where patch recolonization does occur immediately • Colonization and extinction are independent, however they likely show some connectivity. • Habitat corridors may provide increased colonization and immigration, but may also increase rates of disease and pathogens. • Unclear how temporal variability such as primary production of plants effects spatially structured populations
  • 8. Scaling • The form and function of organisms is very diverse and covers a large scale from the largest animals to the smallest units of life. • Empirically, organisms range from 1um to 100 m in size and generation times range from hours to centuries. • Lower limits of size can be explained by the housing of biomolecular machinery that allow cells to function, while upper limits are less clear • The use of power functions ( y=aXb) help describe scaling relationships. • Ex- Metabolic rate= a * massb , where “a” is the conversion factor and “b” is the power function • When b=1, isometric relationship, relationship is constant • When b ≠1, allometric relationship, relationship changes with mass ( 0<b<1) (http://mathbench.umd.edu/modules/misc_scaling/page06.htm)
  • 9. Scaling: Allometric laws • Most power functions when applied to living systems show allometric scaling • Allometric laws are based on empirical observations • Laws help answer questions pertaining to form (surface area and volume, size and strength) and physiological function ( metabolic rate and size, heart rate and size) • Kleiber’s law – metabolic rate (R) is equal to ¾ power of mass • Law applicable from smallest to largest organisms • Also, the ¼ power law can be applied life-span( ~.15-.30, Speakman 2005), where bigger animals with slower metabolism live longer
  • 10. Scaling: Metabolic Theory of Ecology • MTE is an extension of Kleiber’s law which proposes that the metabolic rate of organisms controls ecological processes at all levels of organization ( Brown et al., 2004) • Metabolic rates effect resource uptake from the environment and resource allocation for reproduction, growth, survival • Metabolic rates can influence processes such as life-history traits, population growth rates, and ecosystem processes such as biomass production • Theory takes into account the variables: metabolic rate, temperature, and resource availability. • Ex. One part of MTE states that sp. diversity decreases linearly with inverse temperature
  • 12. Tetragnatha versicolor S. Fork Eel River, 3 sites in viewFeeding experiment enclosures Emerging mayflies Photo credit: Hiromi Uno, 2014 Trapped mayflies in T.versicolor web