The Science of Plant Ecology

Warning! Lab lectures will be included on Lecture Exam #1!

Research Secondary research: Gathering data about facts already known Primary research: Generates new knowledge

Scientific Method Fig. 1.1

Scientific Method Hypothesis: Possible explanation. Must be “testable” by experiment Experiment: Test of idea by observation or collection of data

Experiments Manipulative experiment: Compare treated condition (manipulated) against “control” Control: Keeps other conditions same Fig. 1.2 Konza Prairie (KS)

Experiments Natural experiment: “Manipulative” experiment occurring due to natural process 1980 eruption Mt. Saint Helens, OR

Experiments Observational experiment: Study variation occurring under differing natural conditions Fig. 19.12 Tree species richness (# species) across N. America (in standard area plots) AU!

Theory Theory: Broad, comprehensive explanation of large body of information. Essentially equivalent to “scientific fact” Examples: Theory of gravity, Theory of relativity, Theory of evolution, Atomic theory

Plant Sampling Techniques

Sampling: Why? Best way to find answer is to take 100% sample (count/measure everything) Usually not practical Ex, describe vegetation of Lee County AL

Accuracy vs. Precision Accuracy: how close to “true value” samples are Precision: similarity measurements to each other

Accuracy vs. Precision Accuracy: not known unless 100% sample taken Precision: standard error of mean (S) Standard deviation

Sampling Choosing technique depends on: 1) Desire for accuracy/precision 2) Objective of study 3) Time/money 4) Tradition! Solution: Be reasonable! (compromise often needed)

Importance Often we want to know how “important” plant species are in area 3 measures of importance of a species (sp. A) Density of A = No. inds. per unit area (reflects abundance of A) Frequency of A = No. of times sp. A found in samples divided by total number of samples taken (reflects pattern of A) Cover of A = Percent of area occupied by A in sampled area (reflects biomass of A)

Focus on Cover Many ways to get cover (biomass) data: 1) harvest & measure biomass 2) visual estimation Note how canopy edges “filled in” by observer

Focus on Cover Many ways to get cover (biomass) data: 1) harvest and measure biomass 2) visual estimation 3) point frame

Focus on Cover Many ways to get cover (biomass) data: 1) harvest and measure biomass 2) visual estimation 3) point frame 4) moosehorn crown closure estimator

Focus on Cover Many ways to get cover (biomass) data: 5) Trees: basal area (area tree trunk per unit area). Bitterlich method.

Focus on Cover Many ways to get cover (biomass) data: 6) Trees: DBH (diameter at breast height: 4.5 feet or 1.3 m)

Other Challenges Clonal plants: density (how determine individual?) Canopy overlap: where boundaries? Border calls: in or out? Solution: Be reasonable!

Importance Often we want to know how “important” plant species are in area 3 measures of importance of a species (sp. A) Density of A=No. inds. per unit area (reflects abundance of A) Frequency of A=No. of times sp. A found in samples divided by total number of samples taken (reflects pattern of A) Cover of A=Percent of area occupied by A in sampled area (reflects biomass of A)

Importance Calculate Importance Value (IV) Sum of Relative Density, Relative Frequency, and Relative Cover IV= Rel. density + Rel. frequency + Rel. cover <300%= < 100% + < 100% + < 100%

Sample Techniques 1) Quadrat methods 2 dimensional sample unit used: quadrat Quadrant?

Quadrat Method a) Shape? Oblong better: picks up more variation per sample But: less perimeter means less in/out decisions (source error) Compromise: be reasonable!

Quadrat Method b) Size? VITAL for determining plant pattern (and important for density measurement as well) Can use species-area curve

Quadrat Method c) Number? Suggestions include: A) Sample 1-20% of area B) Include 95% of species C) Use Running Mean Graph (Quadrat Sampling Lab #4)

Belt Transect Method Also 2 dimensional method Useful dense vegetation Useful sampling along sharp environmental gradient 2m 2m Environmental gradient 2m 2m 4 species: A = red, B = turquoise, etc.

Belt Transect Method Example diagram and calculation of Importance Value of species A 2m 2m Environmental gradient 2m 2m 4 species: A = red, B = turquoise, etc.

Belt Transect Method Density of A = 10/40m2 = 0.25/m2 Frequency of A = 9/10 = 0.9 % Frequency of A = 0.9 X 100% = 90% 2m 2m 4 species: A =red, B= turquoise, etc.

Belt Transect Method Cover of A: Assume we visually estimate covers of each species in each unit of transect Assume values for A are: 10%, 15%, 15%, 10%, 0%, 10%, 5%, 5%, 10%, 10% Mean cover of A= Sum of covers/10 = 9% 2m 2m 4 species: A = red, B = turquoise, etc.

Belt Transect Method Do density, frequency, cover calculations for all other species (B, C, D) IV= Rel. density + Rel. frequency + Rel. cover For sp. A: Rel. density = density of A/density of all species X 100% Rel. frequency = frequency of A/frequency of all species X 100% Rel. cover = cover of A/cover of all species X 100% Can then calculate IV for other species (B, C, D)

Belt Transect Method You will do IV calculations for species in lab #1 (plotless sampling) and lab #4 (quadrat sampling) Quadrat lab Plotless lab

Line Intercept Method 1 dimensional method (line has no width) Useful for dense vegetation: scrub Scrub in Australia

Line Intercept Method Cover: record distances along line covered by canopies of species Cover frequency: Divide line into units. Determine frequency of species in those units Density?

Sampling Techniques THE SEQUEL

Plotless (distance) methods Based on points Points have no dimensions: 0 dimensional method Often used with trees: sampling along transect through forest

Plotless (distance) methods Information Collected: 1) tree identity 2) tree size (reflects biomass or cover) 3) distance measurement (from something to something)

Plotless (distance) methods Method 1: Nearest individual method

Plotless (distance) methods Method 2: Nearest neighbor method

Plotless (distance) methods Method 3: Random pairs method A) find nearest tree B) draw line from pt to tree C) make exclusion zone D) measure distance to nearest tree outside zone

Plotless (distance) methods Method 4: Point centered quarter method

Plotless (distance) methods Information Collected: 1) tree identity 2) tree size (reflects biomass or cover) 3) distance measurement (from something to something) IV= Rel. density + Rel. frequency + Rel. cover <300%= <100% + < 100% + < 100% How get rel. density, rel. frequency, rel. cover values?

Plotless (distance) methods Cover: have DBH values Convert DBH to area trunk for each species % relative cover of species Y: Cover of Y/Cover of all species X 100%

Plotless (distance) methods Frequency: Have tree identities for each point % frequency of species Y: No. pts. with species Y/Total number pts. X 100% % rel. freq. of sp. Y: Freq. of Y/Freq. all species X 100% IV= Rel. density + Rel. frequency + Rel. cover

Plotless (distance) methods Density: ?? No areas were measured?? Geometric principle: as density increases distances measured decrease Note importance of random placement of points!

Plotless (distance) methods Steps: 1) Calculate mean distance (D) for all trees sampled 2) Use magic formula: Density (all species) = A/(correction factor)(D)2 To express results in metric units: A=10,000 m2/hectare (ha) D should be in meters (m) Correction factor?

Plotless (distance) methods Steps: Correction factor? 2 for nearest individual method 1.67 for nearest neighbor method 0.8 for random pairs method 1 for point centered quarter method 3) Calculate density of species Y: No. Y/No. all species X Density all species 4) % rel. density of Y: Density of Y/Density all species X 100%

Plotless (distance) methods Can now calculate IV of species Y IV= Rel. density + Rel. frequency + Rel. cover <300%= <100% + < 100% + < 100% Repeat calculations for all other species

Plotless (distance) methods Note on Point Centered Quarter method 1) More data per point 2) Relatively simple 3) No correction factor in density formula (correction factor = 1)

How place sample units? Generally, random best How define? All potential sample units have equal chance of inclusion Why best? Eliminates bias by sampler May be required for statistics or equations (e.g., density formula for plotless methods)

How place sample units? Random not same as: Arbitrary: Choosing while attempting to eliminate conscious bias Systematic: Choosing using numeric pattern (ex, every 5th tree along transect) Deliberate: Choosing with criteria (ex, all trees > 30 cm dbh)

How place sample units? But, random may not always give representative sample Example: X X X X X X X X X X X

How place sample units? Techniques: Random vs. Stratified random (subdivide area & sample randomly in each division)

How place sample units? Techniques: Systematic

How place sample units? Techniques: Random-Systematic (select start randomly, place points on transect systematically: or vice versa) systematic random systematic random OR