TESTING ENERGETIC THEORY WITH

EXPERIMENTAL DEEP-SEA WOOD FALLSCRAIG R MCCLAIN

National Evolutionary Synthesis Center

Dead Wood Tell TalesWOOD FALL

@DrCraigMc

You are free to:!!Copy, share, adapt, or re-mix; Photograph, film, or broadcast; Blog, Tweet, or post video of; !Provide that:!!You attribute the work to its author !#woodfall @DrCraigMc

Biod

iver

sity

Productivity

Productivity Diversity Relationship

THEORIES

OF COMMUNITY

ASSEMBLY AND ENERGETIC

THEORY

(Srivastava & Lawton 1998), originally proposed by Wright (1983) !As productivity decreases, abundances of species also decrease. !Rare species at low productivities are thus at increased risk of stochastic extinction, i.e. Allee effects. !With increased productivity Allee effects are diminished and coexistence increases (Wright et al. 1993).

The Species Energy Theory (More Individuals Hypothesis)

Abun

danc

e

Productivity

Additional energy may elevate the amount of rare resources, allowing rare or absent niche-specialists to become abundant and raise overall community diversity, e.g. Niche Position Hypothesis (Evans et al. 1999; Evans et al. 2005). !At high productivities, this theory also predicts that greater specialization is allowable and prevents competitive exclusion (Schoener 1976; DeAngelis 1994).

Niche Position Hypothesis

Productivity

Spec

ies

Unique Traits

Increased energy may increase the amount of preferred resource, and species may decrease their consumption of less optimal resources. This would reduce niche breadth in high energy areas and allow for greater coexistence, e.g. Niche Width Hypothesis (Evans et al. 1999).

Niche Width Hypothesis

Productivity

Nic

he B

read

th

The food web is predicted to become more complex with increased energy; sustenance to higher trophic levels results in longer food chains (Post 2002a; Takimoto & Post 2012).

One More Trophic Level Hypothesis

Productivity

Trop

hic

Leve

l

An energetic optimum size exists for a community that maximizes multiple energetic constraints that correlate with body size, e.g. metabolism, life history, foraging efficiency, starvation resistance (Rex & Etter 1998; Sebens 2002). Species of this optimum size are more efficient in procuring resources and translating them into growth and reproduction. !More energy allows decreases competitive interactions based on size, i.e. species don’t have to be the perfect size

Nonequitable Distribution of Energy Hypothesis

Productivity

Body

Siz

e

WOOD FALLS

are an IDEAL test system

for theories about COMMUNITY ASSEMBLY AND ENERGETIC THEORY

During the Typhoon Morakot in 2009, a total of 8.4*1012 g of total woody debris

was transported to the oceans of Asia

The total amount of energy can be precisely controlled to the wood fall community.

Discrete habitat boundaries allow for the easy quantification of standing stock, trophic structure, and diversity.

!Easily collected allowing for the whole community to be quantified as

opposed to just the collection of a subset.

Deep-sea wood falls host an almost completely endemic fauna

covering a broad taxonomic composition.

39/43 of the species found on the wood fall were endemic

of these endemic species all were represented by ~10-10,000 individuals, non-endemics have 1-4 individuals

Accurate tracking of energy through the community via stable isotope analysis. !

Stable isotope compositions of animals that rely energetically on wood are isotopically distinct from animals that rely energetically on phytodetritus.

Wood falls in deep sea, especially at the depths investigated here, are also energetically isolated from the surrounding deep sea.

WOOD FALLS

the IDEAL EXPERIMENT

WOOD FALLS

the

RESULTS

Xylophaga

-1.0 -0.5 0.0 0.5

-0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

NMDS1

NM

DS

2

Absent

Light

Present

Weight (kg)

0

5

10

15

McClain & Barry, Biology Letters, 2014

MDS: a matrix of item–item similarities, then assigns a location to each item in N-dimensional space. Distance in plot correlates with differences in communities!!1. Abundance!2. Composition

-30 -20 -10 0 10

010

2030

40

CAP1

CA

P2

Provanna sp. 1

Xyloskenea sp. nov.

Hyalogyra sp. 1

Polynoidae sp. A.Protanais sp. nov.

356

710

1113

18

19

21

22

26 27

30

32

35

Weight

Absent

PresentLight

Occurence of HaloAbsent Light Present

0

100

200

300

400

500

Abun

danc

e Pe

r Woo

d Fa

ll

Protanais sp. nov.

large medium small

0

100

200

0

200

400

0

100

200A

bund

ance

Per

Woo

d Fa

ll

Wood Weight Group

Xyloskenea sp. nov.

Hyalogyra sp. 1

Provanna sp. 1

McClain & Barry, Biology Letters, 2014

Dillwynella (Ganesa) panamesis

Protanais sp. nov.

Set 1

Set 2

November 2006-October 2011 (5 years) multiple successional stages

November 2006-October 2013 (7 years) post halo stage

Species are targeted to a specific log size and successional state Species Energy/Niche Position

P

−1.5 −1.0 −0.5 0.0 0.5 1.0

−1.0

−0.5

0.0

0.5

NMDS1

NM

DS2

1

2

Log Size

MDS: a matrix of item–item similarities, then assigns a location to each item in N-dimensional space. Distance in plot correlates with differences in communities!!1. Abundance!2. Composition

Species are targeted to a specific log size and successional state Niche Position Hypothesis

Presence/Absence−1.5 −1.0 −0.5 0.0 0.5

−0.8

−0.6

−0.4

−0.2

0.0

0.2

0.4

NMDS1

NMDS2

1

2

MDS: a matrix of item–item similarities, then assigns a location to each item in N-dimensional space. Distance in plot correlates with differences in communities!!1. Composition

Biod

iver

sity

Productivity

Productivity Diversity Relationship

1

2

3

4

5

6

7

8

910

11

12

13

14

15

16

17

18

19

20

21

22

2324

26

27

28

29

30

31

32

35

5

10

15

20

0.0 0.5 1.0Log10 Weight (kg)

Ric

hess Set

aa

12

Species Richness Increases With Wood Fall Size Wood Fall Size and Richness Weaker In Second Set

Smaller Wood Falls Become More Diverse

Provanna sp. 1 Provanna sp. 1Provanna pacifica

Xyloskena sp. novHyalogyra sp. 1 Dillwynella (Ganesa) panamesis

Cephalaspidea sp.???

Hyalogyra sp. 1

1

23

45 6

7

8

9

10

11

12

13

14

1516

17

18

19

2021 22

2324

2627

28

29 303132 35

0

500

1000

1500

2000

2500

0.0 0.5 1.0Log10 Weight (kg)

Abun

danc

e

Setaa

12

1078

743

Abundance Increases with Wood Fall Size

1

2

3

4

5

6

7

8

910

11

12

13

14

15

16

17

18

19

20

21

22

2324

26

27

28

29

30

31

32

35

5

10

15

20

1.5 2.0 2.5 3.0Log10 Abundance

Ric

hess Set

aa

12

Richness of Wood Falls Correlated With Abundance More Individual Hypothesis

1

2

3

4

5

6

7

8

9 1011

12

13

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15

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21

22 2324 26

27

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2930

31

32

35

2

4

6

8

0.0 0.5 1.0Log10 Weight (kg)

Sing

leto

ns Setaa

12

1

23

45

6

7

8

910

11

12

13

14

15

16

17

18

19

20

2122

2324

26

27

28

29

30

31

32

35

0

5

10

15

0.0 0.5 1.0Log10 Weight (kg)

No.

of S

peci

es w

/ Abu

ndan

ce L

ess

Than

5

Setaa

12

Number of Rare Species Increases With Wood Fall Size More Individual Hypothesis/Niche Position

Gastropod.1 Gastropod.2 Gastropod.3 Gastropod.4 Gastropod.5 Gastropod.7 Gastropod.8

Gastropod.9 Gastropod.10 Anemone1 Anemone2 Crinoid Ophiuroid.1 Ophiuroid.2

Ophiuroid.3 Bivalve.4 Bivalve.1 Bivalve.2 Bivalve.3 Polychaete.1 Polychaete.2

Polychaete.3 Polychaete.4 Polychaete.6 Polychaete.7 Polychaete.8 Polychaete.9 Polychaete.10

Polychaete.11 Polychaete.16 Polychaete.17 Tanaid.1 Galatheid.1 Galatheid.2 Chiton

Asteroid.1 WTF.1 WTF.2 Amphipod1 Amphipod2 Amphipod3 Pycno1

Iso1 Limpet1 Limpet2

0.00.51.01.52.0

0.51.01.5

0.00.51.01.52.0

0.00.51.01.5

0.751.001.251.50

0.00.10.20.3

−0.050.000.050.10

0.000.050.100.15

0.00.30.60.9

0.00.20.40.6

0.000.010.020.030.040.05

0.00.30.60.9

0.00.20.40.6

0.000.020.040.06

0.0000.0250.0500.0750.100

−0.0250.0000.0250.050

0.00.10.20.30.4

0.00.10.20.3

0.000.020.040.06

0.00.40.81.2

0.00.51.01.5

0.000.250.500.75

0.00.40.81.2

0.00.20.40.6

0.00.10.20.3

0.000.040.080.12

0.000.050.100.150.20

0.0000.0250.0500.0750.100

0.0000.0250.0500.0750.100

0.000.050.100.15

0.000.020.04

0.81.21.62.0

0.00.20.40.60.8

0.00.10.20.3

0.0000.0250.0500.0750.100

0.000.020.040.06

0.0000.0250.0500.075

0.000.05

0.00.30.60.91.2

0.000.250.500.751.00

0.00.10.20.30.40.5

0.0000.0250.0500.075

0.0000.0250.0500.0750.100

0.00.51.0

0.000.250.500.751.00

0.0 0.5 1.0 0.0 0.5 1.0 0.0 0.5 1.0 0.0 0.5 1.0 0.0 0.5 1.0 0.0 0.5 1.0 0.0 0.5 1.0

0.0 0.5 1.0 0.0 0.5 1.0 0.0 0.5 1.0 0.0 0.5 1.0 0.0 0.5 1.0 0.0 0.5 1.0 0.0 0.5 1.0

0.0 0.5 1.0 0.0 0.5 1.0 0.0 0.5 1.0 0.0 0.5 1.0 0.0 0.5 1.0 0.0 0.5 1.0 0.0 0.5 1.0

0.0 0.5 1.0 0.0 0.5 1.0 0.0 0.5 1.0 0.0 0.5 1.0 0.0 0.5 1.0 0.0 0.5 1.0 0.0 0.5 1.0

0.0 0.5 1.0 0.0 0.5 1.0 0.0 0.5 1.0 0.0 0.5 1.0 0.0 0.5 1.0 0.0 0.5 1.0 0.0 0.5 1.0

0.0 0.5 1.0 0.0 0.5 1.0 0.0 0.5 1.0 0.0 0.5 1.0 0.0 0.5 1.0 0.0 0.5 1.0 0.0 0.5 1.0

0.0 0.5 1.0 0.0 0.5 1.0 0.0 0.5 1.0Log10 Weight (kg)

Abun

danc

e Set

1

2

Responses of Individual Species Vary

The food web is predicted to become more complex with increased energy; sustenance to higher trophic levels results in longer food chains (Post 2002a; Takimoto & Post 2012).

One More Trophic Level Hypothesis

Productivity

Trop

hic

Leve

l

Conclusions• Species richness increases with increasing wood fall size

• With greater time the relationship becomes weaker

• With time, smaller logs add species with greater magnitude that larger logs

• Abundance increases with increasing log size and in second set (more time)

• Richness is a function of abundance among wood falls (Species Energy)

• But more species for same abundance in second set

• Second set is more even (adding more species without increasing abundance)

• Addition of rare species (Island biogeography, Niche Position)

• Number of singletons more pronounced in smaller logs (Allee Efffects, Species Energy)

• However, rare species seem to contribute to overall all richness in both sets with increasing wood size (Niche Position)

• Abundance of all species do not increase at the same rate (Niche Position)

Acknowledgments

Jim Barry (MBARI), Jenna Judge (UC Berkeley), David Honig (Duke U), Janet Voight (Field Museum), Tammy Horton (NOC), Doug Eernisse (UC Fullerton), Keiichi Kakue (Hokkaido U) !Funding: National Evolutionary Synthesis Center (NSF Grant #EF-0905606) !Funding and Ship Support: Monterey Bay Aquarium Research Institute (Packard Foundation) !Artwork by Immy Smith Visiting Artist, Herbarium RNG

@DrCraigMc

Deep Sea News

Deep SeaNewsDS

N

http://deepseanews.com

http://craigmcclain.com

Df Sum Sq Mean Sq F value Pr(>F) Weight 1 46950 46950 26.0946 3.717e-07 *** Species 44 815908 18543 10.3063 < 2.2e-16 *** Set 1 10825 10825 6.0162 0.0143 * Weight*Species 44 432523 9830 5.4635 < 2.2e-16 *** Residuals 1349 2427164 1799

Abundance of all species is expected to increase with increasing wood-fall size. !Wood-fall size is predicted to be a significant predictor of abundance. The size*species interaction term should not be statistically significant, i.e. different relationships—negative and positive—between size and abundance for each species

More Individuals Hypothesis

Df Sum Sq Mean Sq F value Pr(>F) Weight 1 46950 46950 21.3099 4.256e-06 *** Set 1 10825 10825 4.9131 0.02681 * Rank 1 414815 414815 188.2776 < 2.2e-16 *** Weight:Rank 1 99176 99176 45.0142 2.807e-11 *** Residuals 1435 3161605 2203

Niche Position HypothesisAdditional energy may elevate the amount of rare resources, allowing rare or absent niche-specialists to become abundant and raise overall community diversity !Abundance of rare species only increases with increasing wood-fall size. !The abundance rank order, a metric of dominance/rarity, is expected to show a significant interaction effect with size, i.e. high rank order species have slopes near zero and low rank order species have positive slopes.

Species Rank

Spec

ies

Abun

danc

e

12

510

2050

100

1 2 3 4 5 6 7 8 9 10 11 12

Species Rank

Spec

ies

Abun

danc

e

12

510

2050

2 4 6 8 10 12 14 16

3

5

6

7

10

11 13

18

1921

22

26

27

30

32

35

1

24

8

9

121415

16

17

20

2324

28

29

311.0

1.5

2.0

2.5

3.0

0.0 0.5 1.0Log10 Weight (kg)

Coe

ffici

ent f

rom

Zip

f Fit

Setaa

12

3

5

6

7

10

11

13

18

19

21

22

2627

3032

35

1

24

8

9

12

14

1516

17

20

2324

2829

310.2

0.4

0.6

0.8

0.0 0.5 1.0Log10 Weight (kg)

K fro

m G

eom

etric

Ser

ies

Setaa

12

Log 32

Log 35