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Environmental Ecology Lab
Stream Ecology:Density Independence Versus Density Dependence In Streams
Presented By- Mamun Md.Master’s Degree Dept.- Bioscience and BiotechnologyMajor Field-Biodiversity and Environmental EcologyStudent Id-201650783Session -2016,Spring
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Contents: Introduction Characterization of Stream systems Objectives Density Independent Mechanism Density Dependent Mechanism Density-dependent factors Density-independent factors Implication of density dependence Existence of density dependent factors in stream systems Experimental evaluation of various density dependent
mechanisms in stream systems Support density independent regulation as the major factor
regulating organisms in stream systems by Researchers Dominance of Density Independence – Is It valid?
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Contents: Testing Stream Systems for Density Regulating Mechanisms Functional group concept How density dependence can conduct by using Grazers? Several Problems arise during study of density dependent
interactions by using grazers Mechanisms of detritus in stream ecosystems Stream detrital dynamics model Conclusion
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Introduction:
♣ Descriptive Science
♣ Taxonomy has been a major thrust
♣ Describe basic structure of stream communities
♣ Life histories of some species
♣ Examine functional relationships within stream community
♣ Formalization of the functional group concept, RCC concept
♣ Recognition the importance of detritus and instream autotrophy
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Characterization of stream systems:
♣ Annual floods
♣ Occasional catastrophic floods
♣ Pulsed periods of detrital input
♣ Seasonal temperature changes
bed of the stream is subject to both erosion and deposition
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Objectives: ♣ To know about density independence factors
♣ To gain knowledge about density dependent factors
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What are the density independent and density dependent mechanisms?
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Density independent mechanism: ♣ Catastrophic mechanism which act independently of the
density of the population being affected ♣ Like, a spate or sudden freeze ♣ After passing that event population contain exponential
growth.
Density dependent mechanism: ♣ Change in intensity as a function of population density ♣ Like, predation , competition and parasitism. ♣ When the population increases , the influence of density
dependent mechanisms also increases ♣ Reduction in population growth = intrinsic rate of population’s
growth
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Density-dependent factors:A factor that depends on population size is called a density-dependent factor.
Density-dependent factors include: ♣ Competition ♣ Predation ♣ Parasitism ♣ Disease ♣ Territoriality ♣Waste Accumulation ♣Migration
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Density-independent factors:Density-independent factors affect all populations in similar ways, regardless of the population size.
Examples of density-independent factors include:
♣ Unusual Weather ♣ Natural Disasters ♣ Seasonal Cycles ♣ Certain Human Activities—such As Damming Rivers
And Clear-cutting Forests ♣ Fire ♣ Flood Weather ♣ Volcanic Eruption ♣ Chemical Pesticides
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Implication of density dependence: ♣ Population is controlled by food supplies or floods
♣ Concern reproductive strategies, diversity and the general applicability of equilibrium based ecological theory
♣ More applied scale – management strategies , impact assessment and prediction
♣ Assemblages of opportunists rearrange the community structure( Paine, 1966,1669)
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Existence of density dependent factors in stream systems:
♣ Impact of predaceous flatworms in restructuring a stream community ( Macan,1962)
♣ Factors influencing the distribution of lotic Trichoptera (Edington, 1965)
♣ Physical factors set as distributional template and territorial behavior was the ultimate regulating mechanism(Edington, 1965)
♣ Support the competitive exclusion principle(Allan, 1975)
♣ Microhabitat segregation found between two congeneric harpacticoid copepods (Shiozawa,1978)
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Experimental evaluation of various density dependent mechanisms in stream systems:
♣ Manipulation of invertebrate in cages and conclude that movements were density dependent (Peckarsky,1979)
♣ Competitive interactions among benthic grazers (McAuliffe and Hart)
♣ Found significant differences in leaf pack decomposition rates(Oberndorfer et.al)
♣ Perhaps the best known working hypothesis is the excess production hypothesis(Waters 1961, 1965, 1966)
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♣ Excess production hypothesis relates behavioral drift to assimilation and secondary production above the carrying capacity
♣Manipulated food level in artificial streams and significantly found more drift with lower concentrations(Hildebrand, 1974)
♣ No significant change in stream benthos after trout were excluded from Colorado stream (Allan, this volume)
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Support density independent regulation as the major factor regulating organisms in stream systems by Researchers:
♣ Factors controlling benthic invertebrates in running waters and 90% discussion was density independent mechanisms(Hynes,1970)
♣ No community of running water may considered as climax and a climax community implies equilibrium conditions and Violence of flow is the main regulatory mechanisms(Margalef, 1960)
♣Headwater stream communities as assemblages of opportunists(Patrick,1972)
♣ Opportunists inhabits in headwater streams of temperate area(Stout and Vandermeer,1975)
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Dominance of Density Independence – Is It valid?
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Yes , it is valid due to four reasons.
1. Major factor regulating stream community structure
2. High diversity that exists in temperate streams
3. Support highly variable distribution of stream benthos
4. Predominantly a descriptive science
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1. Major factor regulating stream community structure:
♣ Effects of three catastrophic floods caused major restructuring of the stream ecosystems( Hynes, 1972)
♣ Snow melt with ice jam effect downstream community structure in several kilometers( Shiowzawa)
♣Summer cloud bursts caused catastrophic changes in community structure
♣Long term dynamics of a single community is nonexistent and density dependence , like density independence ,need to operate continually(macArthur,1972; Wiens,1977)
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2. High diversity that exists in temperate streams:
♣ Diversity may develop from a patchy environment induced by density independent factors
♣ Few major contradictions noted by MacArthur when compare with tropical diversity
♣ Inferior species increase the community diversity
♣ Intermediate disturbances are important factors in controlling diversity in both tropical coral reefs and tropical forests and undergoing succession by uncolonized cells or patches ( Connell,1978and 1979)
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3. Support highly variable distribution of stream benthos :
♣ Support correlative field relationship depend on physical factors
♣ Most familiar example , sampled a “ relatively uniform riffle “ and estimate community density with 95% Confidence(Needham and Usinger, 1956)
♣ Improved the quantitative nature of sampling gear( Waters and knapp,1961; Mundie ,1971)
♣ Refined statistical methodology(Elliott,1977)
♣Benthic sampling depend on plot type sampling technique ,one square foot
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♣ Increasing the area during sampling on heterogeneous conditions improved the precision of Data
♣ processing of samples in the laboratory can be simplified by statistics( Cochran,1963;green ,1979 et.al) and equipment (Waters,1969;Mundie 1971)
♣ Plotless techniques ( Shiozawa,1978) and reduced sampler area improve resolution of habitat grain (Elliott,1977)
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4. Predominantly a descriptive science:
♣ Basic approach is sample survey
♣ sample numbers converted to densities or biomass and give a picture about stream community structure
♣ After advent of computer and statistical packages data seta gain more validity and interpretations obtain more legitimacy
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Two basic problems arise with statistical methodology:
♣ First, As we measure the parameters through our intuition which is biased by our own limited ability in perceiving all potential causal factors
♣ Stream ecosystems analyzed by using two components . I. Abiotic components( often field observed)II. Biotic components( often laboratory derived)
♣ Second, Sampling survey can not prove causality
♣ Statistics based on sample surveys do not make definitive conclusions about causality
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Testing Stream Systems for Density Regulating Mechanisms:
♣ Formulation of logical hypotheses♣Mathematical modelling(give precise predictions and opportunity of formulating biological relationships and observing “noiseless “ system changes according to these relationships)
How hypotheses can be tested? ♣ Very extensive sampling-type surveys ♣ Experimental manipulation
Experimental manipulation is probably the best approach for the stream researchers
Here causality can be demonstrated
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How benthic community regulated by the factors?
♣ Not all members of the benthic community are regulated by the same factors
♣some are regulated by predation , others by food , space or density independent factors
♣ The community include organisms of different trophic levels and different functional groups( Cummins,1974;cummins and Klug,1979) across these levels
♣In a community the manipulation of one factor may only influence a few species and the other species might show no effect
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Functional group concept: ♣ Functional designations are mutable(Merritt and
Cummins,1978)
♣Organisms may specialize differentially within separate communities( Fox and Morrow,1981) and thus have different functional roles in those communities.
♣Within a community a given species may perform several functions
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How density dependence can conduct by using Grazers?♣High densities of mountain suckers (Pantosteus platyrhynchus) occurred in some pools and were in low densities in others in the Raft River ,Idaho
♣ The riffles adjacent to pools containing high sucker densities had low filamentous algal cover
♣Mountain suckers are grazers( Scott and Crossman,1973) and helps in structuring the local algal communities
♣Exclusion of grazers from the tiles resulted in an increase in algal biomass( Lamberti and Resh,1980)
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Several Problems arise during study of density dependent interactions by using grazers:
♣ First, the influence of seasonality on density dependent interactions
♣ Factors such as canopy, angle of the sun , turbidity and water temperature vary seasonally and influence the production rate of autotroph and instream primary production will not remain constant (Hickman,1974)
♣ Second, many aquatic organisms grow in cohorts
♣ Biomass is confounded with time
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Use of production rates avoid these two problems:
♣ Excess production hypothesis not only invokes density dependence as a regulating mechanism, but also converts the mechanism into one related to energy flow and production
♣ Drift acts as a mortality factor
♣Probability of mortality is higher in drifters (Allan,1978;Waters,1972)
♣ Measurement of primary and secondary production is not easy and normally conducted in unmanipulated field conditions
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Mechanisms of detritus in stream ecosystems: ♣ Most detritus is introduced in Autumn leaf fall in stream in
temperate climates
♣ Leaves are colonized and turn into food for detritivores (Cummins,1974)
♣ Carrying capacities increase by annual pulsing of leaf litter
♣ Subsequent increase of CPOM and then transfer into MPOM and FPOM , respectively and then into DOM
♣ Leachate and other DOM flocculate (Lock and Hynes, 1975 and 1976) and make up a significant portion of fines(Boling et.al.,1975)
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♣ FPOM fluctuate annually ( Hynes et.al., 1974)
♣ High degree of age and species specificity in the filter net size implies some degree of specialization to the food resources being exploited ( Wallace et al., 1977)
♣ Periods of food scarcity (Weins,1977) are most likely to occur during the periods of decline of the pulses
♣Shredder community can also be predicted by using K of leaf material
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Stream detrital dynamics model:♣Predict changes in leaf standing stock with different storage capacities of the stream systems
♣ Rate of leaf decomposition in a stream is related to factors like leaf species, shredder abundance , water temperature and location of the leaf material in the stream(cummins et.al;1973 and so on.
♣ if detritus decomposition and processing is location specific (Meyer,1980) then the standing stock of leaf material will be a function of the diversity locations.
♣ Decomposition slower in reducing environments ♣ depositional regions(pools) contain low amount of oxygen but
erosional regions(riffles) contain high amount of oxygen because of turbulence
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♣ Simulation was run with continuous litter input and the results behave as anticipated (Fig.1 and 2)
♣ Low riffle ratio (high pool) stored more material than the high riffle system
♣ Litter input is pulsed , not continuous and the levels of material resulting in streams with differing storage capacities
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♣ A simple function(Dixon,1976) was used which allowed a changing rate of leaf fall ( Fig.3)
♣ Systems with high proportions of riffles tend to have more pulsed leaf litter standing stock in the areas. Input of the leaves from terrestrial system and subsequent leakage is dominant (Fig.4)
♣Systems with low riffle ratio (Fig.5) and high pool ratios have less pulsed leaf litter standing stocks
♣ impact of leakage from the system is buffered by leakage to the riffle from the pool storage(Fig.6)
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♣ This model is still being modified and data collected from valley Creek, Minnesota and have some assumptions
♣ While general predictions are still accommodated, storage capacities and leakage rates differ more than originally assumed
♣ These variations will probably increase the differences between riffle –pool ratios rather than diminish them
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♣ Density dependence will be more likely in the high riffle ratio systems
♣ Here leaves for shredding should become limiting rapidly
♣ High storage capacity streams have more gradual leakage to the riffles
♣Assimilation ratio of riffles to pools related to total secondary production rates
♣Increased secondary production from increased riffle area may reduced storage capacity of stream
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♣ Leaf pack decomposition approximates a negative exponential curve(Petersen and Cummins,1974)
♣ If leaf pack size sets K, K will eventually approach zero
♣ Shredder curve shows an initial colonization pulse and subsequently , smoothly tracks the declining K
♣ Drift occurs in a diel pattern , the feeding activity patterns of drifting organisms are likely to be diel also
♣ Oscillations of K depend on microorganisms growth rates with time and nutrients
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Conclusion: ♣ Streams are complex systems
♣ Their complexity does not make them impossible subjects for study of density dependent and independent factors
♣ It based on sound hypothesis and experimental design
Thank you for kind attention