Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
SlideShare a Scribd company logo

Variability and Organisms

•Download as PPTX, PDF•
•
Robin Shin
Robin Shin

This document summarizes key concepts in ecology related to variability in organisms and populations. It discusses how genetic variability and environmental heterogeneity lead to no two organisms or species being identical. It also describes metapopulation dynamics and how populations are maintained through dispersal and the processes of extinction and recolonization between habitat patches. Finally, it discusses scaling relationships in biology from molecules to ecosystems and how metabolic theory can help explain ecological patterns and processes across levels of organization.

1 of 15
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

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