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Basic metrics of food webs PowerPoint PPT Presentation


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Basic metrics of food webs. A pitcher plant ( Nepenthes albomarginata ) food web . Nepenthes albomarginata. S = 19 species L max = 19*18/2 = 171 possible links between two species L = 35 realized links between two species Connectance : C = 35/171

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Basic metrics of food webs

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Basic metrics of food webs

Basic metrics of foodwebs

  • A pitcher plant (Nepenthes albomarginata) food web

Nepenthes albomarginata

S = 19 species

Lmax = 19*18/2 = 171 possiblelinksbetweentwospecies

L = 35 realizedlinksbetweentwospecies

Connectance: C = 35/171

Ch = 100 totallength of allfoodchains

Li = 40 isthetotalnumber of chains

ChL = 100/40 = 2.5 istheaveragechainlength

L/S = 35/19 = 1.8 isthemeannumber of links per species


Basic metrics of food webs

Foodwebmetricstranslatedintomatrixmetrics

N = 28

Fill = 28/80=0.35

Dm=28/10=2.8

Dn=28/8=3.5


Basic metrics of food webs

Metrics of speciesassociationsinbiogeographicmatrices

TheC-score as a metric of negativeassociations

Checkerboards

TheClumping-score as a metric of positiveassociations

TheTogetherness-score as a metric of nicheoverlap


Basic metrics of food webs

Theadditivenature of theC-score

Numbers of checkerboards for entrieswithinthearea AT are a measure of spatialspeciesturnover.

Numbers of checkerboards for entrieswithinthearea ATC are a measure of turnover independent speciessegregation.

CMixed = CS – CTurn - CSegr.

Therankcorrelation of matrixentriesis a metric of spatialturnover.

  • 11 21 32 12 2…….7 108 10

R2is a moreliberalmetricthanCturn.

R2 = 0.347

Thecorrelation of ordinationscoresisalso a metric of turnover but even less selective.


Basic metrics of food webs

Rangesizecoherence

Coherentrangesize

Scatteredrangesize

Thereare 17 embeddedabsences.

Thenumber of embeddedabsencesis a measure of speciesrangesizecoherence.

Themetricdependsstrongly on theordering of rows and columns


Basic metrics of food webs

Themeasurement of nestedness

Thedistanceconcept of nestedness.

Sort thematrixrows and olumnsaccording to some gradient.

Define an isoclinethatdividesthematrixinto a perfectlyfilled and an empty part.

Thenormalizedsquared sum of relativedistances of unexpectedabsences and unexpectedpresencesisnow a metric of nestednessis.


Basic metrics of food webs

Nestedness based on Overlap and Decreasing Fill (NODF)

NODF is a gap basedmetric and moreconservativethantemperature.


Basic metrics of food webs

The disorder measure of Brualdi and Sanderson

Ho many cellsmust be filledoremptied to achieve a perfectlyorderedmatrix.

TheBrualdiSandersonmeasureis a count of thisnumber

Discrepancyis a gap countingmetric.


Basic metrics of food webs

How to measurespeciesaggregation?

dij

Nearestneighbormetrics

Nearestneighbouris a presence – absencemetric

Compartmentedmatrix

NND hasweakpowerathighermatrixfill

Joincountstatistics

Othermetricsproposed:

Morisita

Simpson

Soerensen

Block variance

Ordinationscorevariance

Marginalvariances

A sum of cellentriesaround a focalcellmultiplied by theentry of thefocalcell

Joincountoperates on presence – absence and abundancematrices

Thesemetricshaveverylowpower a moderate to smallmatrixsize and high orlowmatrixfill.


Basic metrics of food webs

Abundancebasedmetrics

TheC-scoreextension

The metric CA is a count of the number of abundance checkerboards in the matrix.

Other 2x2 submatricescatchmatrixpropertiesthathave not welldefinedecologicalmeaning.


Basic metrics of food webs

Nestednessinabundancematrices

Themetricis a sum of allpairsinthematrix (first sortedaccoding to speciesrichnessthensortedaccording to weights), wheretheweightintherow/column of lowerspeciesrichnessissmallerthantheweightintherow/column of higherspeciesrichness


Basic metrics of food webs

A completetable of methods for co-occurrenceanalysis


Basic metrics of food webs

Patterndetectioninlargematrices

Pajek: software for socialnetworkanalysis

WAND: ecologicalnetworkanalysis

Theseprogramsuseclusteranalysis and ordination to sort thematrixaccording to numbers of occurrences. Didstancemetricsarethenused to identifycompartments.

Theygeneratehypothesesaboutmatrixstructure.

They do not fullyallow for statisticalinference.

KliqueFinder: software for compartmentanalysis


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