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Spatial Statistics. Jonathan Bossenbroek, PhD Dept of Env. Sciences Lake Erie Center University of Toledo. What is Spatial Statistics?. The quantitative study of phenomena located in space. Spatial patterns Autocorrelation Semivariance Example – Moose on Isle Royale.

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spatial statistics
Spatial Statistics

Jonathan Bossenbroek, PhD

Dept of Env. Sciences

Lake Erie Center

University of Toledo

what is spatial statistics
What is Spatial Statistics?
  • The quantitative study of phenomena located in space.
    • Spatial patterns
    • Autocorrelation
      • Semivariance
    • Example – Moose on Isle Royale
where are people in bowman oddy
Where are people in Bowman-Oddy?

Are they randomly distributed?

point to point nearest neighbor analysis
Point-to-Point Nearest-Neighbor Analysis
  • Uses distances between points as its basis.
  • The distance observed between each point and its nearest neighbor is compared with the expected mean distance that would occur if the distribution were random.
g statistic
G Statistic
  • di is the distance of point i to its nearest neighbor
  • y is distance
  • n is the number of points
slide7

Distance

Examples: paint splatters, dandelions in a field, …

slide8

Distance

Examples: breeding birds, beach blankets,

slide9

Distance

Examples: Buffalo at a watering hole, fast food restaurants, …

slide10

How old are those people in Bowman-Oddy?

Are they randomly distributed?

geostatistical tools for modeling and interpreting ecological spatial dependence
Geostatistical Tools For Modeling And Interpreting Ecological Spatial Dependence
  • Ecological Monographs 62(2). 1992. pp. 277-3146 1992 by the Ecological Society of America
  • Richard E. Rossi et al.
  • “…geostatistics is never a replacement for sound ecological reasoning”
geostistical tools
Geostistical Tools
  • Spatial and temporal dependence are the norm in natural systems:
    • Different plant species are often different on north and south facing slopes.
    • Grasshoppers are more dense during hot dry periods.
  • Spatial dependence is particularly important in analysis of spatially varying organisms and environmental variables.
  • Spatial statistics can test for independence!
always know your data
Always know your data!
  • Rossi et al. suggest always beginning with exploratory data analysis.
    • Histograms, regressions, scatter plots etc.
basic statistics do not tell the story
Basic statistics do not tell the story
  • Two statistical tools:
    • h-scatterplots
    • Variography
  • h-scatterplots
    • displays the degree of spatial continuity or correlation at some lag distance h
  • Variograms
    • Variograms model the average degree of similarity between the values of a variable as a function of distance.
scatter plots
Scatter plots
  • Typical scatter plot compares measurement of two parameters at the same location or of the same object.
  • h-scatter plots compares measurement of the same parameter at a certain distance apart.
semivariance
semivariance

A variogram summarizes all h-scattergrams for all possible pairings of the data or rather distributes variance across space.

  • y(h) is the estimated semivariance for lag h
  • N(h) is number of pairs of points separated by lag h
  • Z(xi) is the value of variable Z at location xi
  • Z(xi + h) is the value of variable Z at location xi + h
looking back at h scatter plots
Looking back at h-scatter plots…
  • What is the variance at h = 1?
  • Is the variance at h = 2 > or < h = 1?
semivariogram

Sill

Semivariance

Nugget

Range

semivariogram

Distance (h)

1 2

semivariogram27

Sill

Semivariance

Nugget

Range

semivariogram

Distance

semivariogram28
Semivariogram
  • Sill
    • Variance level equivalent to the global variance of the area
  • Range
    • Distance at which data are no longer spatially autocorrelated.
    • Patch size?
  • Nugget
    • Represents micro-scale variation or measurement error.
other topics in spatial statistics
Other topics in spatial statistics.
  • Kriging: an interpolation method for obtaining stastically unbiased estimates for field attributes (yield, nutrients, elevation) from a set of neighboring points.
other topics in spatial statistics33
Other topics in spatial statistics.
  • Correlogram: a measure of spatial dependence (correlation) of a regionalized variable over some distance
other topics in spatial statistics34
Other topics in spatial statistics.
  • Metapopulation Models: A set of partially isolated populations belonging to the same species. The populations are able to exchange individuals and recolonize sites in which the species has recently become extinct.
spatial patterns in the moose forest soil ecosystem on isle royale michigan usa j pastor et al
Spatial patterns in the moose-forest-soil ecosystem on Isle Royale, Michigan USA – J. Pastor et al.
spatial patterns in the moose forest soil ecosystem on isle royale michigan usa j pastor et al37
Spatial patterns in the moose-forest-soil ecosystem on Isle Royale, Michigan USA – J. Pastor et al.
  • Observations:
  • Hypotheses:
  • Results:
spatial patterns in the moose forest soil ecosystem on isle royale michigan usa j pastor et al38
Spatial patterns in the moose-forest-soil ecosystem on Isle Royale, Michigan USA – J. Pastor et al.
  • Observations:
    • Moose preferentially forage on aspen and avoid conifers.
  • Hypotheses:
    • If moose browsing causes a shift in dominance from hardwoods to conifers across adjacent areas, we should expect corresponding changes in soil nutrient availability over the landscape.
  • Results:
what was the study about
What was the study about?
  • Examine the largescale landscape distribution of moose browsing intensity in relation to plant community composition and size structure, as well as soil nitrogen availability.
    • Do moose control plant community composition and soil nitrogen at large scales?
what did they measure
What did they measure?
  • Available browse.
  • Annual consumption by moose.
  • Soil nitrogen availability.
what did pastor conclude
What did Pastor conclude?
  • No differences in nitrogen availability or consumption due to slope or aspect.
    • Spatial patterns not caused by topographic relief.
  • Patterns are a result of dynamic interactions between moose foraging and plant communities.
  • Uncommonly strong impact for a large mammal.
  • This patterns has occurred in less than 50 generations.
why are things spatially autocorrelated
Why are things spatially autocorrelated?
  • Environment
    • Examples: soil, climate, moisture, ...
  • Interactions
    • Examples: competition, herbivory, mutualism