“Soft” Approaches to Regional Species Pools for Plots

Tom Wentworth, Jason Fridley, Joel Gramling, Todd Jobe

Ecoinformatics Working GroupNovember 25, 2002

What is a regional species pool? Bob Ricklefs (TEON, 5e, 2001):

“The species that occur within a region are referred to as its species pool. All the members of the regional species pool are potential members of each local community.”

Local communities are subsets of the regional species pool. More from Bob Ricklefs (TEON, 5e,

2001): “A central concept of ecology is that membership in local communities is restricted to the species that can coexist together in the same habitat. Thus, each local community is a subset of the regional species pool.”

Work of Weiher and Keddy…

Species sorting: experimental study of 20 wetland species seeded into 120 wetland microcosms representing varied environments

Bob Ricklefs (TEON, 5e, 2001): “Interactions of species within local habitats make up only half of the diversity equation.”

Regional vs. Local Effects

So what? The relationship between the regional

species pool and local community is mediated by important processes fundamental to our understanding of how local communities are organized: dispersal habitat selection predatory and competitive exclusion chance extinction

Interesting questions: (1) Is there proportional sampling vs. saturation?

Interesting questions: (2) What is the extent of nestedness?

We gain important insights from examination of species pools.

Our Challenge: Building Species Pools We don’t know

the species pools contributing to our plots: we could accept

arbitrary definitions, but…

objective approaches are preferable: is there a bottom-up approach?

“Hard” vs. “Soft” Approaches (sensu Fridley) Hard: species are associated with one

another through co-occurrence in plots: species pools are built through “chains” of co-

occurrence among species Soft: species pools are constructed as

plots/species are accumulated by “proximity”: geographic (limited utility, but traditional) environmental (attractive as we gather data) compositional (most accessible)

Soft Pools: Geographic Basis Place plots in a geographic space

(x, y, maybe z): select a plot accumulate species in the regional

pool from nearest neighbor plots add species until…when???

Soft Pools: Geographic Basis We don’t think this is necessarily the

best idea: no well-defined stopping point accumulating species through geographic

proximity builds pools with “strange bedfellows” (consider the longleaf savannah adjacent to a pocosin)…

but perhaps this is consistent with Ricklefs’ definition of regional species pools?

Soft Pools: Environmental Basis Place plots in an environmental space

select a plot accumulate species in the regional pool

from nearest neighbor plots add species until you…

reach a plot that shares no species with starting plot

reach some arbitrarily determined distance

Soft Pools: Environmental Basis We like this idea:

support from work by Taylor, Aarssen et al.

builds pools using plots that are initially similar from an environmental perspective

NCVS data base is richly endowed with environmental data

Soft Pools: Compositional Basis Place plots in an compositional space

select a plot accumulate species in the regional pool

from nearest neighbor plots add species until you…

reach a plot that shares no species with starting plot

reach some arbitrarily determined distance

Soft Pools: Compositional Basis We like this idea:

builds pools using plots that are initially similar from a compositional perspective

not restricted by limited availability of environmental data

Soft Pools: Alternatives Plot-based environmental and

compositional spaces can also be populated with species: why not build pools based on

species’ centers and accumulate these in a nearest-neighbor approach?

a nice start, but ignores differential niche breadths of species…

STND01

STND02

STND03

STND04

STND05

STND06

STND07

STND08

STND09

STND10

STND11

STND12STND14

STND15

STND16STND17

STND18

STND20

STND21

STND22

STND23

STND24

STND25

STND26

STND27

ACRU

ACSA

AMAR

BENI

CACA

CAGL

CATO

CECA

COFL

DIVI

FAGRFRAM

FRPE

ILOP

J UVILIST

LITU

MATRMAVI

MORU

NYSY

OSVI

OXAR

PIEC

PITA

PRSE

QUAL QUCO

QUFAQUMA

QUMI

QUNI

QUPH

QURU

QUST

QUVE

SAAL

ULAL

ULAM

ULRU

CACO

Class data

Axis 1

Axi

s 2

Soft Pools: Alternatives Plot-based environmental and

compositional spaces can also be populated with species: why not build pools based on distributions

of species overlapping a particular plot?

environmental or compositional gradient

STND01

STND02

STND03

STND04

STND05

STND06

STND07

STND08

STND09

STND10

STND11

STND12STND14

STND15

STND16STND17

STND18

STND20

STND21

STND22

STND23

STND24

STND25

STND26

STND27

ACRU

ACSA

AMAR

BENI

CACA

CAGL

CATO

CECA

COFL

DIVI

FAGRFRAM

FRPE

ILOP

J UVILIST

LITU

MATRMAVI

MORU

NYSY

OSVI

OXAR

PIEC

PITA

PRSE

QUAL QUCO

QUFAQUMA

QUMI

QUNI

QUPH

QURU

QUST

QUVE

SAAL

ULAL

ULAM

ULRU

CACO

Class data

Axis 1

Axi

s 2

Problems… How many axes for environmental or

compositional space? as number of axes increases, species

pool collapses to the species present in the plot

could limit analysis to n compositional or complex environmental axes (from PCA), but how many?

Edge effects limit detectability of species pools for marginal plots