UBC BLISS talk 2016

50
Cascading effects of spatial structure across trophic levels Rachel M. Germain Killam/Biodiversity Postdoctoral Fellow Main collaborators: Natalie Jones, Tess Grainger, Ben Gilbert, Andrew MacDougall

Transcript of UBC BLISS talk 2016

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Cascading effects of spatial structure across trophic levelsRachel M. GermainKillam/Biodiversity Postdoctoral Fellow

Main collaborators: Natalie Jones, Tess Grainger, Ben Gilbert, Andrew MacDougall

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Community ecologist: species coexistence and metacommunities

Schematic modified from Velland 2016

Botany seminar Oct. 11th @12:30pm

env gradient

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Collaborators

Tess Grainger Natalie Jones Ben Gilbert

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Biological communities rarely exist in isolation

‘metacommunity’

biotic/abiotic environment

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Predictions of island biogeography/metapopulation theories

species richness/site occupancy larger, less isolated patches

species richness/site occupancy smaller, more isolated patches

MacArthur & Wilson 1967; Hanski 1994

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Predictions of island biogeography/metapopulation theories

species richness/site occupancy larger, less isolated patches

species richness/site occupancy smaller, more isolated patches

MacArthur & Wilson 1967; Hanski 1994

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Spatial constraints likely vary among species

sessile vs. motile, dispersal ability, cognitive function → behavior (habitat selection, territory, predator avoidance), body size, matrix sensitivity, etc.

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P

C2

C1

C3

Cascading spatial dynamics among trophic levels

patchisolation

patchsize

spatial patterns

spatial patterns

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Multi-trophic extensions of island biogeography and metacommunity theories

Trophic dependency: predators can only establish in patches that already contain their prey• prey must outpace their predators• predator distributions should be a subset of prey distributions• IBT patterns should be stronger at higher trophic levels

Holt 2002 EcoRes; Leibold et al. 2004 EcoLett; Harvey & MacDougall 2014 Ecology

Assumes that predators: are specialists, are bound to same habitat patches as their prey, and experiencethe world at the same spatial scales as their prey

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What are the consequences for diversity in systems where spatial constraints differ within and among trophic levels?

aspen-understory plantsJones, Germain, et al. 2015 JEcology

tall-grass prairie plantsGermain et al. 2013 AmNat

milkweed insect specialistsGrainger, Germain, et al.

in review Ecology

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What are the consequences for diversity in systems where spatial constraints differ within and among trophic levels?

aspen-understory plantsJones, Germain, et al. 2015 JEcology

tall-grass prairie plantsGermain et al. 2013 AmNat

milkweed insect specialistsGrainger, Germain, et al.

in review Ecology

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Tall-grass prairie restoration efforts in SW Ontario

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System: tall-grass prairie plant communities

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System: tall-grass prairie plant communities

How does risk avoidance behavior by small mammals affect spatial patterns in plant communities?

predationrisk

cognition

yes

yes

no

rangesize

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Predation risk increases with distance from old-field edge

pre-prairie

more removal less removal

old-field

Prediction:

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Closedold-field Pre-prairie

-30 -10 10 30 50 70 90+

Distance from edge (m)

Prop

. see

ds re

mov

ed

F1,84 = 150.9, P < 0.0001*

Seed removal was strongest in the old-field, and decreased with distance from the edge

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Consequences of small mammals for plant diversity depends on foraging selectivity

Cafeteria trial w/ 8 plant species from 3 functional groups

B. kalmii H. divaricatus R. blanda

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H. annus

H. dive

ricatus

L. capita

ta

R. blanda

S. trifo

lia

S. cryp

tandrus

B. inerm

is

B. kalm

ii0

2

4

6

8

10

Seed species

Seed

s rem

aini

ng

Forb seeds were consumed significantly more than shrub and grass seeds

Functional group: F2,23 = 29.97, P < 0.001*Species: F5,23 = 0.35, P = 0.876

Forbs Shrubs Grasses

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P = 0.012*F1,48 = 12.82, P <0.001*

β-di

vers

ity (J

acca

rd’s

diss

imila

rity)

α-di

vers

ity (s

peci

es p

er p

lot) α β

Distance from edge (m) Distance from edge (m)

What does this all mean for plant community distributions?

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What does this all mean for plant community distributions?

P = 0.012*F1,48 = 12.82, P <0.001*

β-di

vers

ity (J

acca

rd’s

diss

imila

rity)

α-di

vers

ity (s

peci

es p

er p

lot) α β

Distance from edge (m) Distance from edge (m)

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oldfield

increasingβ-diversity

decreasing seed

predation

prairie interior

Net effect: emergent patterns in plant diversity that reflect risk environment

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What are the consequences for diversity in systems where spatial constraints differ within and among trophic levels?

aspen-understory plantsJones, Germain, et al. 2015 JEcology

tall-grass prairie plantsGermain et al. 2013 AmNat

milkweed insect specialistsGrainger, Germain, et al.

in review Ecology

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System: milkweed insect specialistshabitat use

generalist

milkweedspecialist

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Milkweed specialists differ in susceptibility to predators and dispersal ability

Constrained by predation1:

yes

1Duffey & Scutter 1972, Zalucki & Kitching 1982, Smith et al. 2008 2Jones & Parella 1986, St Pierre & Hendrix 2003, McCauley et al. 1981

no

yes no

Constrained by size/isolation2:

<100 m >1000 m

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Predictive framework for island biogeography informed by natural history

P, S, I

S, Inone

P

Patc

h oc

cupa

ncy

Patch size/isolation

P = predator, S = size, I = isolation

Do constraints of patch size/isolation vary among species, and are they altered by predation?

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Field surveys of milkweed patches

Patch isolation

Patch size (m2)

𝐼 𝑖=1−∑𝑗 ≠𝑖

𝑛

𝐴 𝑗𝑒(−𝑑 𝑖𝑗 /𝛼 )

Hanski 1994 TREE

Presence/absence data Predator abundances

occupancy ~ patch size x patch isolation x predator abundances

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Predictive framework for island biogeography informed by natural history

none

P

N.S.

Patch isolation

Occ

upan

cy

P, S, I

S, I

P = predator, S = size, I = isolation

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Predictive framework for island biogeography informed by natural history

none

PP = predator, S = size, I = isolation

P, S, I

S, I

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Predictive framework for island biogeography informed by natural history

none

PP = predator, S = size, I = isolation

P, S, I

S, I

Zalucki & Kitching 1982a JZoology, Zalucki & Kitching 1982b Oecologia

“More eggs were laid per plant on single isolated plants than on plants within a patch”

“The trend was for increasing [mortality] with increasing patch size” → predation

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Predictive framework for island biogeography informed by natural history

none

PP = predator, S = size, I = isolation

P, S, I

S, I

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Tying it all together…

Dispersal-limited species were directly affected by spatial constraints

Predation affected palatable species indirectly through interactions with spatial drivers

Incorporating predator-avoidance tactics (refuge seeking and crypsis) can help refine predictions

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Biogeographic constraints highly variable among species in this community – but fairly predictable

Matrix-dwelling predators can weaken or modify the effects of spatial drivers

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What are the consequences for diversity in systems where spatial constraints differ within and among trophic levels?

aspen-understory plantsJones, Germain, et al. 2015 JEcology

tall-grass prairie plantsGermain et al. 2013 AmNat

milkweed insect specialistsGrainger, Germain, et al.

in review Ecology

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System: Aspen understory plant communities

Do effects of stand size and isolation on species distributions vary with dispersal mode?

cognition

yes

no

rangesize

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Field surveys of aspen stands

𝐼 𝑖=1−∑𝑗 ≠𝑖

𝑛

𝐴 𝑗𝑒(−𝑑 𝑖𝑗 /𝛼 )

Hanski 1994 TREE

Stand characteristics

size (m2) isolation

stand age

Presence/absence data Dispersal mode

No aid

Wind

Animal

Aspen stand

Adjacent grassland

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Predicted effects of stand size and isolation for different dispersal modes

No aid Wind-dispersed Animal-dispersed

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Observed effects of stand size and isolation for different dispersal modes

No aid Wind-dispersed Animal-dispersed

competition among dispersal modes?

ruderal species and disturbance?

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Paired plot design to identify aspen specialists vs. generalists or grassland specialists

Quantifying species affinity for aspen stands

all species includedoccurs in aspen stands ≥50% of the timeoccurs in aspen stands ≥ 66% of the timeoccurs in aspen stands ≥75% of the time

cut-off is not always clear in “diffuse” metacommunities

Cook et al. 2002 EcoLett; Leibold et al. 2004 EcoLett

metacommunity = species that occur in favourable habitat patches imbedded in a matrix of unfavourable habitat

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The results are insensitive to cut-off, except when all species are included

SR ~ stand size

Matrix-associated species can obscure metacommunity processes – paired plot design is one day to discount their effects

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IBT patterns are somewhat consistent with our initial predictions, but …There are three complicating factors:• dispersal mode• unexplained inconsistencies • grassland specialists + generalists

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…and so, to summarize…

ability to persist in matrix habitat = modifications to biogeographic constraints in insect species that are sensitive to predators

greater habitat use by granivores in low risk areas = gradients in ecological filters that dictate plant species distributions

habitat selection by animals = non-IBT patterns for animal-dispersedplant species

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“patch area and isolation are surprisingly poor predictors of occupancy for most species”

data from 1,015 bird, mammal, reptile, amphibian, and invertebrate population networks

metapopulation metacommunity∑ =

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Island biogeography in non-island systems

suitable habitat unsuitable habitat

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Island biogeography in non-island systems

suitable habitat unsuitable habitat

Are patch size and isolation unimportant compared to/in combination with local factors? How do spatial dynamics cascade across trophic levels? How do spatial dynamics change with species additions or losses at different trophic levels? Should conservationists only be focusing on patch size/isolation?

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AcknowledgementsCo-authorsNatalie JonesTess GraingerBen GilbertAaron HallLynn BaldwinAndrew MacDougallKarl CottenieLaura JohnsonElizabeth Gillis

Webpage: rgermain.wordpress.com Email: [email protected]: BIODIV245

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Monarch caterpillar mortality as a function of stand size

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PCoA testing turnover in proportion of species belong to each dispersal modes

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