Seed Predation Along an Elevational Gradient in the Tropical Andes, Peru

SEED PREDATION ALONG AN ELEVATIONAL GRADIENT IN THE TROPICAL ANDES, PERU

RACHEL HILLYER

A Thesis Submitted to the Graduate Faculty of

WAKE FOREST UNIVERSITY

in Partial Fulfillment of the Requirements

for the Degree of

MASTER OF SCIENCE

in the Department of Biology

May 2009

Winston-Salem, North Carolina

Approved By:

Miles R. Silman, Ph.D., Advisor ______

Examining Committee:

Kathleen A. Kron, Ph.D. ______

William K. Smith, Ph.D. ______

ACKNOWLEDGEMENTS

From the start, I’d like to thank my advisor, Dr. Miles Silman, for his patience, thoughtful guidance, and constant enthusiasm throughout this entire process. I’d also like to thank the members of my committee, Dr. Kathleen Kron and Dr. William Smith for lending their time and perspective to this project. I’ve also benefited from the support and insight of the entire Silman lab: Dr. Ken Feeley, Julie Wyatt, Josh Rapp, William Farfan Rios, and Karina García Cabrera. I am also indebted to Mireya Natividad Raurau Quisiyupanqui both for the use of the seed rain data and for being my middleman in Peru. I owe a huge thank you to my field assistants in Peru: Jhoel Delgado Salazar, Guido Vilcahuaman Fernandez, Reyner Tairo Loayza, and Adam Ccahuana Quispe for their many hours of hard work. Funding for this research was provided by the Moore Foundation. I’d like to thank my mom, dad, and brother for the love and support that brought me here. Finally, to my fellow grad students who became my closest allies: Heather Fairfield, Jacquelyn Grace, Paige Roe, and Hugh Bender, thanks for the never ending support when things were difficult and all the laughter when things were fun.

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TABLE OF CONTENTS

LIST OF TABLES……………………………………………………………………….v

LIST OF FIGURES………………………………………………………………………vi

ABSTRACT……………………………………………………………………………..vii

INTRODUCTION………………………………………………………………………...1

Differential Seed Predation on Plant Species …………………………………….2

Biotic Interactions along Gradients…………….…………………………………3

Predicting Extinctions Due to Climate Change………………………………..….4

METHODS………………………………………………………………………………..5

Study Site………………………………………………………………………….5

Study Species……………………………………………………………………...5

Seed Predation Experiments………………………………………………………6

Ecosystem Productivity Data..…………………………………………………….7

Analysis……………………………………………………………………………8

RESULTS…..……………………………………………………………………………10

Seed Predation…………………………………………………………………...10

Predictors of Seed Predation…………………………………………………..…11

DISCUSSION………………………………..…………………………………………..11

Species Differences…………………….………………………………………...11

Species-Elevation Interactions…………………………………………………...13

Alternative Hypotheses for Seed Predation Patterns.……………………………15

The Importance of Gradients in Biotic Interactions……………………………..16

LITERATURE CITED…………………………………………………………………..18 iv

FIGURE CAPTIONS……………………………………………………………………26

TABLES………………………………………………………………………….……...27

FIGURES………………………………………………………………………………...35

CURRICULUM VITAE…………………………………………………………………45

LIST OF TABLES

TABLES PAGE

1. Species used in seed predation experiments……………………………………..27

2. Elevation midpoints of species and genera……………………………………....28

3. Dates of installation and censuses of seed predation sites……………………….29

4. Cox proportional hazard model of seed survival………………………………...30

5. Generalized linear model of seed mortality vs. seed mass ……………………...31

6. Linear regressions of species seed mortality vs. elevation midpoints of genera...32

7. Linear regression of species seed mortality vs. elevation midpoints of species...33

8. Linear regression of measures of ecosystem productivity vs. elevation…………34

LIST OF FIGURES

FIGURES PAGE

1. Experimental design………………………………………………………….35

2. Boxplot of species seed mortality …………………………………………...36

3. Seed mortality across the elevation gradient ………..……………………....37

4. Patterns of species seed mortality across elevation …………………...…….38

5. Seed mortality vs. seed mass………………………………………………...39

6. Seed mortality vs. elevation midpoint of genera…………………………….40

7. Seed mortality vs. elevation midpoint of species…………………………….41

8. Seed rain volume vs. elevation………………………………………………42

9. Woody biomass increment vs. elevation…………………...………………..43

10. Elevational ranges of rodents and carnivores in Manu National Park……….44

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ABSTRACT

The study of plant species response to climate change is primarily a study of plant distributions along environmental gradients, on which biotic interactions exert a large impact. Post-dispersal seed predation is a plant animal interaction that affects the population dynamics, community structure, and diversity of plant species through time and space. This thesis presents a comparative seed predation study of 24 species of tropical trees across a 2.5 km elevation gradient in the Peruvian Andes. The following questions were asked (1) does seed predation vary across the elevation gradient? (2) do predation rates vary among species and are those rates predictable from species traits such as seed size or current elevational range? And (3), what may be the underlying cause of variation in seed predation rates in terms of ecosystem productivity and associated animal communities? Species exhibited marked variation in total seed predation and in seed predation across the elevation gradient. For all species combined there was a significant decrease in seed predation at high elevations, resulting in an 5.6 increase in effective fecundity for trees at 3450 m. The overall trend in seed predation across elevation potentially arises due to seed predator regulation via top-down forces in the lowlands giving way to bottom-up (productivity) regulation at mid to high elevations.

INTRODUCTION

The study of plant species responses to climate change is at its core a study of species distributions along environmental gradients. Most research in this area, both modeling (see Malcom et al. 2002; Thomas et al., 2004 for overviews) and empirical work (e.g. Ibañez et al., 2008) focus on changes in abiotic gradients. However, biotic interactions are central to plant distributional ecology, and changes in biotic interactions can have profound effects on species distributions (Weltzin et al., 1997; Leathwick and

Austin, 2001; Webb and Peart, 2001). Indeed in a major empirical study of plant responses to climate change, a treatment intended to “control” for seed predators had effects on plant recruitment that equaled or exceeded climate treatments (Iabñez et al.,

2008). How plant-animal interactions change across environmental gradients, even through central in setting plant distributions, is little studied.

Post-dispersal seed predation is a quantitatively important plant-animal interaction that can control population dynamics in time and space (Janzen, 1971; Hulme, 1998;

Silman et al., 2003). Seed predators affect plant populations through changes in population dynamics (Harper, 1977; Crawley, 2000), community structure (Howe and

Brown, 1999), and species diversity (Hubbell 1980). In long-term studies of the population dynamics of tropical trees, Silman et al. (2003) and Wyatt and Silman (2004) found that population fluctuations in a major seed predator (white-lipped peccary) controlled recruitment of the two dominant tropical tree species (Astrocaryum murumuru and Iriartea deltoidea) in Western Amazonia. Rodents as seed predators have been shown to have considerable impact on plant populations (Price and Jenkins, 1986), and 2 this can occur in manifold ways, such as controlling the desert grassland transition

(Brown and Heske, 1990), affecting the landscape level abundance of early successional species (Orrock et al., 2006), and reducing seed recruitment in tropical canopy trees (De

Steven and Putz, 1984; Schupp, 1990). Seed addition experiments suggest that seed limitation is important in many different terrestrial habitats (Silman, 1996; Svenning and

Wright, 2005; but see Hulme, 1998; Crawley, 2000) and when seeds have been protected from herbivores, all protected seeds have ultimately germinated (Wenny, 2000). Changes in seed predation have also been shown to interact with other species interactions to radically alter distance- and frequency-dependent recruitment in tropical trees, a central mechanism maintaining diversity in tropical forests (Janzen, 1970; Connell, 1978; Wright and Duber, 2001; Wyatt and Silman, 2004).

Differential Seed Predation on Plant Species

Differential seed predation on plant species is reported in many studies (e.g.

Wilson and Whelan, 1990; Terborgh et al., 1993; Holl and Lulow, 1997; Blate et al.,

1998; Notman and Gorchov, 2001; Xiao et al., 2006), and the relative effects on species can vary widely. In a study of grassland plants the seed predation of different species ranged from 20 to 95% though there was no difference in the percentage of times species were encountered by seed predators (Hulme, 1994). In the Chilean Andes seed removal ranged from 3 % to 78 % across nine species of herbs and shrubs (Muñoz and Cavieres,

2006). The effect of seed predation on the population dynamics of species can also vary.

Seed predation significantly reduced seedling populations of two of five Papua New

Guinean tree species (Cerbera floribunda K. Schum. and Microcos grandiflora Burret) 3 while the seedling populations of the other three species were only minimally affected

(Jones et al., 2008).

Multiple suggestions for species differences in predation risk have been proposed.

Seed size can have multiple effects, from changing the suite of predators to which a species is exposed, to nutritional return on search and handling time (Louda, 1989; Blate et al., 1998). Seed size may also affect predation risk indirectly through differences in germination rate, which in turn affects the period of time a seed is at risk of predation

(Silman 1996, Baraloto and Forget, 2007). Size-independent effects that affect predation risk include variability in secondary chemistry (Janzen, 1969), caloric content (Kear,

1962), nutritional content (Kelrick et al., 1985), and seed density (Nilsson and Wästljung,

1987). Hulme (1993) relates predator preference to seed size and shape, nutritional content, and toxicity. These seed traits may only affect predation rates in specific situations as studies have found no preference by rodents for energetic content of seeds

(Kerley and Erasmus, 1991) or no relationship between seed mass and predation risk

(Moles et al., 2003).

Biotic Interactions along Gradients

Ecology was founded on the study of species distributions along environmental

gradients in response to abiotic factors (e.g. Cowles, 1899; Clements, 1916; Gleason,

1926; Whittaker, 1956), and that tradition continues today in bioclimatic niche modeling

(see Elith et al., 2006 for a thorough review). However, biotic interactions that have

quantifiable impacts on plant populations can also change over environmental gradients.

In populations of a temperate shrub (Haplopappus squarrosus H. and A.), seed predation

varies along an elevation gradient, seedling recruitment is proportional to the number of 4 seeds surviving predation, and juvenile recruitment is proportional to the number of seedlings established (Louda, 1982). For example, the allocation of resources to growth by cacti influences the fecundity of the cacti’s insect herbivores across time and space

(Miller et al., 2006). Decreasing ant abundance at increasing elevations decreases seed dispersal of the common understory herbs Trillium and Hexastylis in temperate forests

(Zelikova et al., 2008). The abundance of and the damage caused by cactus eating insects decreases with elevation (Miller et al., 2009). In alpine grasslands, seed predation is higher at 2700 m than 2000 m due to the increased activity of ants and birds at the higher elevation (Muñoz and Arroyo, 2002). In shrub lands seed predation was lowest at mid elevations where vegetation provides more safe sites for seeds than the types of vegetation at high and low elevations (Rey, 2002). All of these factors may affect plant distributions in ways that greatly modify the relationship between plant distributions and the abiotic environment.

Predicting Extinctions Due to Climate Change

Changes in species distributions along environmental gradients of temperature and moisture form the foundation for predictions of species responses to global climate change (Malcom et al., 2002; Thomas et al., 2004). In humid tropical systems, species extinctions are tied to species abilities to migrate to higher elevations rather than latitudinally, as in temperate systems (Colwell et al., 2008). Recent studies from Earth’s highest biodiversity hotspot, the tropical Andes, predict a 4°C warming (Cramer et al.,

2004). Given the adiabatic lapse rate of 5.5 °C km-1, temperature changes of this 5 magnitude require that species must migrate upslope ~700-800 m by 2100 to remain in equilibrium with climate, with recent studies predicting that migration rates less than equilibrium lead to large-scale extinctions (Silman, 2007; Feely and Silman, in press).

This thesis presents a comparative seed predation study of 24 species of tropical trees across a 2.5 km elevation gradient in the Peruvian Andes, representing ~14°C of temperature change, to ask (1) does overall seed predation vary across the elevation gradient? (2) do predation rates vary among species? If so, are predation rates predictable from species traits such as seed size or current elevational range? And (3), what may be the underlying cause of variation in seed predation rates in terms of ecosystem productivity and associated animal communities?

METHODS

Study Site

The study was performed in the Kosñipata Valley on the southeastern flank of the

Peruvian Andes (13° 06’ S, 71° 36’ E; see www.andesconservation.org for more information on the field site). In 2003 a network of 14 1 ha permanent plots was established along an elevation gradient in primary montane forest from 800 m to 3450 m.

Eleven of the permanent plots were used in this study (Fig. 1a), nine of which also fall within the boundaries of Manu National Park. Climate along the gradient is wet, with annual precipitation ranging from 8 m in the lowlands to 2.4 m in the highlands, and mean annual temperatures ranging from 23 – 8.5°C with increasing elevation. All trees

≥ 10 cm dbh (diameter at breast height [1.33 meters]) have been tagged and identified to 6 species. The majority of seed predators are thought to be rodents, but birds and insects, particularly ants, consume seeds as well. Data for mammal communities in the area come from Solari et al. (2006), birds from long-term and extensive surveys by multiple investigators started in the 1970s (Terborgh et al., 1984; Walker et al., 2006) and ant data from Webb (2008).

Study Species

The twenty-three native tree species used in this study (Table 1) were chosen to represent a range of seed sizes and elevational ranges (species that grow in low, mid, and high elevations). A tropical grass, Zea mays L., is considered to be edible by a broad variety of rodents and was used as a control along the gradient. Seeds were collected in

July 2008 by searching the permanent plots and the forests at Wayqecha Cloud Forest

Research Center (~3000 m) and Pantiacolla Lodge (400 m). Seeds were gathered from ripe fruits in the canopy or from beneath parent trees. Voucher samples were collected from parent trees to confirm identification of species used. Only mature seeds with no visible signs of damage were used in experiments, and all fleshy pulp was removed from seeds manually. For species in the Arecaceae seeds include the stony endocarp that surrounds the endosperm, whereas the entire fruit (pericarp) has been removed from the seeds of the other species. Elevational ranges of genera and species were derived from plot records (ABERG, 2009). Ranges were determined by taking the elevational midpoint of each genus or species, accounting for the abundance of each genera/species at each elevation (Feeley and Silman, in press).

Seed Predation Experiments

Experimental sites were established in August and September 2008 at eleven 1 ha plots (Fig. 1a). Seed sites were located adjacent to previously installed fruit and seed traps, with 25 seed sites stratified across each 1 ha plot (Fig. 1b). For three species, I. deltoidea, Dictyocarium lamarkianum, and Z. mays, there were sufficient seeds to place three seeds at each site, which was done to increase sample size. A single seed of the remaining 21 species was used so that there were thirty seeds placed at each site. Seeds were placed in a 5 x 6 array with 10 cm separating each seed (Fig. 1c). All seeds were surrounded by an 8 cm high mesh screen inserted 3 cm into the dirt. The screen was to delineate an area in which to search for seeds during recensuses and to prevent them from washing away in high rainfall and was not adequate to exclude potential seed predators.

A total of 8,250 seeds were placed: 750 at each elevation, 275 of each species (825 of I. deltoidea, D. lamarkianum, and Z. mays) and 25 seeds of each species at each elevation

(75 of I. deltoidea, D. lamarkianum, and Z. mays).

Predation experiments were recensused approximately 1, 4, and 10 weeks from the date of installation (exact dates are listed in Table 3). Seeds were marked as absent if they could not be located within the bounds of the mesh fence. Seeds that remained were recorded as being intact, bitten, moldy, with larva, or germinating.

Ecosystem Productivity Data

Data on seed rain and woody biomass increment were used as indirect proxies for productivity in order to examine the relationship between ecosystem productivity and seed predation rates across the gradient. Data from one year of bi-weekly collections of 8 seeds and fruits from the 275 traps across the gradient were used for information on the total biomass of seeds produced (M. N. Raurau, n.d.). Volume was calculated for each

4 2 seed by modeling it as an ellipsoid [( /3)πlw , where l is the measurement of the longest

dimension of the seed, and w is the measurement of the shortest dimension]. Annual seed

rain measurements include all seeds collected in litter traps from February to December

2007. Seasonal seed rain is the portion of seeds collected from August to November, the

months in which seed predation experiments were installed and censused. Annual woody

increment data were collected from dendrometers measurements of ~300 randomly

chosen trees ≥ 10cm dbh in 1 ha tree plots at each elevation (ABERG, 2009).

Analysis

All analyses use seed mortality totals from the third census at 10 weeks. Seed mortality includes seeds that were bitten and absent seeds. The assumption was made that seed removal equaled predation. Vander Wall et al. (2005) outline the objections to

this assumption, with the main objection being that seed removal may be functioning as

secondary dispersal, not predation, as removed seeds are sometimes cached and remain

viable. However, a literature review shows that <10% of all seeds removed are

secondarily dispersed, and that within these, survival and germination from cached seeds

is low (as seed predators return to eat the cached seeds) for both temperate and tropical

species: Quercus spp., 1.5-2.5% (Jensen and Nielsen, 1986); Fagus grandifolia, 0-4%

(Jensen, 1982); Gustavia superba, 0.75-10% (Forget 1992); Dipteryx panamensis, 0-2%

(Forget, 1993). Additionally, the mortality of seedlings germinating from cached seeds is high (Forget, 1993; Vander Wall, 1994). Finally, if seed removal is an overestimate of 9 actual seed predation, this overestimation is made across all elevations.

Predation risk was modeled using failure-time analysis. Proportional hazards failure time models are used when treatments are thought to increase the risk during times of hazard, but not the timing of the hazard itself (Fox, 2001). A Cox proportional hazard regression (Cox, 1972) was run using JMP v. 3.2.2 (SAS Institute Inc., Cary, NC, 1989-

2007). In a proportional hazards model, negative coefficients represent a decrease in the hazard, thereby increasing the time to failure. Locally weighted scatter plot smoothing

(LOESS), a non parametric regression technique was used to fit lines through mortality data. This method estimates the response of points individually, giving more weight to points near the point for which the response is being estimated. LOESS does not require the specification of a function (like linear or logistic regression) to fit a model, so it is useful for modeling processes for which there are no theoretical expectations (Cleveland and Devlin, 1988).

Seed mass, annual seed rain volume, and seasonal seed rain volume were log transformed and percent mortality was arcsine transformed to meet assumptions of normality. Linear regression was used to determine the relationship between elevation and annual seed rain volume, seasonal seed rain volume, and woody biomass increment.

Linear regression was also used to model the seed mortality of species as a function of the elevational range of genera and the elevational range of species. Elevational ranges of genera were used as the seeds of congeners may share traits that make species indistinguishable to rodents. A generalized linear model with a quasi-binomial error distribution (to accommodate overdispersion of the data) was used to model the relationship between species level seed mortality and seed mass (Crawley, 2005). 10

Spearman rank correlations were used to compare mortality at each elevation with annual seed rain volume, seasonal seed rain volume, and wood growth. All analyses were done using R v. 2.6.2 (R Development Core Team, 2008).

RESULTS

Seed Predation

There was high variability in the average predation rate for each species, from as low as 59% in Meliosma vasquezii, to as high as 97% in Zea mays (Fig. 2; Species main effect, p<0.001, Table 4). Mortality was not constant over elevation (Fig. 3; Elevation main effect, p<0.001, Table 4). The survival of seeds (1 – mortality) increased 5.6x between 2250m and 3450 m, (Pr(survive) 0.10 to 0.56; Fig. 3).

For all species, seed mortality was not constant over the elevation gradient, and there was high variability in the pattern of predation on each species over the gradient

(Fig. 4; Species by Elevation interaction, p<0.001, Table 4). The five smallest seeds

(mass of 5 – 20 mg): Heliocarpus americanus, Hesperomeles ferruginea, Solanum sp.,

Myrica pubescens, and Hyeronima oblonga, have 100% mortality at 1000 m and then gradually decline to 60 – 80% mortality over the gradient (Fig. 4). Many of the other species, namely Tapirira guianensis, Myrcia sp., Mollinedia sp., Prunus detrita, Protium sp., Matisia malacocalyx, Coussarea ecuadorensis, D. lamarckianum, and I. deltoidea, closely follow the elevational trend seen for all species combined. Ormosia sp. and M. vasquezii also appear to follow the overall trend despite high plot to plot variation (Fig. 4).

Zea mays was the only species to exhibit near constant, high mortality at all elevations. 11

Predictors of Seed Predation

Neither seed mass, elevational range, nor seasonal or annual measures of seed and ecosystem productivity were significant predictors of seed predation rates. Seed mortality exhibited no relationship with seed mass (linear regression, p=0.46, Table 5;

Fig. 5). There was no relationship between the elevational midpoint at the genus (linear regressions, Table 6; Fig. 6) or species level (linear regressions, Table 7; Fig. 7). Woody biomass production and annual seed production both decreased significantly with elevation (linear regressions; wood growth: p=0.001, Table 8, Fig. 9; seed volume: p=0.03, Table 8, Fig. 8a), though the trend in seasonal seed rain volume did not (p=0.12;

Table 8; Fig. 8b). However, neither wood growth (Spearman’s rho, ρ = 0.2909; p=0.52), annual seed rain volume (Spearman’s rho, ρ = 0.1091; p=0.74), or seasonal seed rain volume (Spearman’s rho, ρ = -0.2182; p=0.38) are correlated with seed mortality at each elevation.

DISCUSSION

This study assessed seed predation rates across an elevation gradient running from the Amazonian lowlands to Andean tree line using 24 species with elevation ranges varying over 3 km and seeds ranging in size over four orders of magnitude. The study found a large and significant effect of elevation on overall predation rate, large and significant differences among species, and clear differences in the way that predation rates varied among species across the elevation gradient. Across the elevation gradient large and small-seeded species responded differently to changes in ecosystem 12 productivity and the associated seed predator community. The conclusions of this study highlight the importance of taking gradients of biotic interactions into account when considering species distributions.

Species Differences

Seed predation rates varied markedly among species, as demonstrated frequently in the past (e.g. Wilson and Whelan, 1990; Holl and Lulow, 1997; Blate et al., 1998;

Notman and Gorchov, 2001; Xiao et al., 2006). Species also differed in their response to elevation (Fig. 4), demonstrating that the interaction between species and seed predators is changing with elevation, and in response to factors that vary among species. One species trait measured in this study was seed mass, which was not a significant predictor of seed mortality; large seeds were not eaten more frequently than small seeds (Fig 5).

Results from seed predation studies are equivocal in the importance of seed size on predation, with it found to be a significant predictor of seed predation risk in some studies

(e.g. Louda, 1989; Hulme, 1993; Silman, 1996; Blate et al., 1998), and not in others (e.g.

Holl and Lulow, 1997; Meiners and Stiles, 1997; Moles et al., 2003). Given the broad range of seed sizes used in this study, finding no effect of seed size on predation risk without considering elevation is likely due to the fact that while a single type of predator may prefer a particular seed size (Mendoza and Dirzo, 2007), the combined community of predators may have no preference, such as when rodents prefer to eat larger seeds and ants prefer to eat smaller seeds (Mittelbach and Gross, 1984). This result signifies that the community of seed predators in the Kosñipata Valley is sufficiently broad to handle seeds of all sizes. 13

Species-Elevation Interactions

Although there was no relationship between seed size and predation risk when elevations were aggregated, seed size did lead to important differences in how seed predation risk changes with elevation in different species. Small seeded species and large-seeded species show different patterns in the relationship between seed predation risk and elevation. The pattern exhibited by the five smallest seeds is markedly different from that of other species (Fig 4). The mortality of these species at the lowest elevations is higher than the mortality of large-seeded species, probably because seeds of all sizes faced predation from rodents, but only small seeds faced additional predation from ants

(Mittelbach and Gross, 1984). Ants are established predators on seeds small enough for them to handle (Davidson, 1977; Levey and Byrne, 1993) and can negatively impact plant recruitment (Feldmann et al., 2000). The increased predation from ants would gradually diminish along the elevation gradient as ant abundance also decreases with elevation (Webb, 2008).

The seed predation risk of most other large-seeded species peaks at mid elevations

(~2250 m) and then gradually decreases (Fig. 4). This pattern, the same pattern seen across the elevation gradient when species are aggregated (Fig. 3), appears to be driven by elevational variation in seed predator abundance. Seed predation can vary directly with seed predator populations; abundant seed predators eat more seeds (Schnurr et al.,

2002). Previous studies that have shown decreased effects of herbivores on plant populations over elevation have attributed this decrease to a reduction in herbivore abundance (Zelikova et al., 2008 and Miller et al., 2009). Seed predator abundance is set both from the “top” by predators, and from the “bottom” by resource productivity. Top- 14 down forces can have important effects in tropical forests (e.g. Terborgh et al., 2006), but it has also been hypothesized that the strength of top down regulation in a system decreases when productivity decreases (Oksanen et al., 1981; Polis, 1999). Several studies have supported this hypothesis in tropical terrestrial ecosystems (Loiselle and

Faji-Brener, 2002; Richards and Coley, 2007). In a system regulated by bottom up forces, as productivity decreases, so do seed predator populations, thereby decreasing herbivory.

Two measures of productivity available for the Kosñipata Valley, wood growth and seed rain volume, decrease with elevation. It is likely then that at high elevations reduced productivity is limiting seed predator populations and thereby limiting seed predation

(although there is no direct correlation with seed mortality and productivity at the plot level).

While the decreasing trend in seed mortality from mid to high elevations is evident; less clear is what is happening at elevations 1000 m and lower. Total seed mortality was lower at 1000 m than at elevations from 1500 to 2500 m (Fig. 3), a decline that may be plot to plot variation or the beginning of a decreasing trend in seed predation, giving seed mortality a unimodal response to elevation. The same balance of top down and bottom up control of seed predator communities used to explain the high elevation decrease also explains the low elevation decrease. Lowland forests are controlled by top down forces, so that seed predator populations, and thereby seed predation, are reduced by carnivores (Silman et al., 2003; Terborgh et al., 2008). Low elevations have the productivity to support high populations of seed predators, but seed predators are held below carrying capacity by top down forces. Carnivore populations decrease with elevation (Fig. 10), releasing pressure on seed predators. Released from carnivore 15 pressure, seed predator populations reach carrying capacity which is eventually reduced at high elevations by limited productivity.

Alternative Hypotheses for Seed Predation Patterns

There is a strong case for changes in seed predator abundance driving seed predation patterns, but there are several alternative hypotheses that should be considered.

Predator satiation hypotheses predict that seed survival will be higher during times of seed abundance (Janzen, 1969; Schupp, 1990). Predator satiation can operate on a specific and a community level, where the total presence of seeds an in area affects the predation of a single species (Janzen, 1971). In this study, predator satiation, at least at the community level, is an unlikely explanation for patterns as annual seed volume decreased with elevation (where predation was also lower) and there was no relationship with seasonal seed volume.

Other seed traits (not quantified in this study), such as secondary chemistry

(Janzen, 1969), caloric content (Kear, 1962), and nutritional content (Kelrick et al., 1985), might cause differential seed predation among species, but would not be expected to influence elevational patterns of predation risk, unless also considered in conjunction with seed predator and carnivore abundance. Of the three of the genera represented in this study with documented toxins in their seeds [quinolizidine alkaloids in Ormosia spp.

(Kinghorn et al., 1988), glycoalkaloids in Solanum spp. (Cipollini and Levy, 1997), and cyanogenic glycosides in Prunus spp. (Frohne and Pfänder, 2005)], none had lower than average mortality. 16

Finally, the novelty of seed predators/species interactions could influence predation patterns along the gradient. In this study, high elevation species were moved down range and low elevation species were moved up, so that all species were exposed to predation in both novel and familiar territories. Two scenarios from the plant invasion literature can be applied to this situation: the natural enemies hypothesis and the biotic resistance hypothesis (Maron and Vilà, 2001). The natural enemies hypothesis suggests that exotic species invade new areas easily because they are freed from the co-evolved predators and herbivores in their native habitat (Elton, 2000). The biotic resistance hypothesis suggests the opposite, that exotics fail to invade new areas because they are strongly hindered by interactions with native species (Elton, 2000). Migrating species, while not the foreign invaders typically considered in these hypotheses, are species trying to establish under a novel suite of biotic interactions. If migrating species follow the natural enemies hypothesis, low elevation species should experience lower predation at high elevations. Under biotic resistance, predation on lowland species at high elevations will equal or be greater than the predation on highland species. However, at none of the elevations in this study was there a significant relationship between seed mortality and the elevation midpoint, so neither the natural enemies or biotic resistance hypothesis appear to be relevant to the patterns shown in this study. Variation in seed predator abundance is the most likely driver of the significant variation in seed predation risk seen in this study.

The Importance of Gradients of Biotic Interactions

Abiotic factors such as temperature and precipitation are typical elements of 17 bioclimatic models of species range predictions (Bakkenes et al., 2002; Thomas et al.,

2004). As shown in this study and others, there are also gradients of biotic interactions which are less frequently taken into account when predicting species ranges (Davis et al.,

1998). Furthermore, the gradient in seed mortality translates into a large change in effective fecundity for trees at high elevations. Trees growing at 3450 m can produce the same number of seeds as their lower elevational counterparts, yet could potentially have five times as many seeds available for establishment. Fecundity rates are essential parameters in models predicting plant species migration rates (Pakeman, 2001; Higgins et al., 2003) as migrating species are essentially dispersing into an empty landscape, where there are no adults to supplement seed availability. For example, pines compete well in post-fire landscapes in part because of their high fecundity rates (Richardson and Higgins,

1998). What remains to be answered is what impact this large change in fecundity has on tree demography (sensu Yamada et al., 2007; Brodie et al., 2009).

LITERATURE CITED

ABERG. 2009. Permanent tree plot network. www.andesconservation.org

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FIGURE CAPTIONS

Figure 1. Experimental design: (a) 11 one hectare permanent plots along an altitudinal transect in the Kosñipata Valley, (b) 25 seed predation sites in each 1 hectare plot, and (c) 30 seeds at each site, 3 of I. deltoidea, D. lamarkianum, and Z. mays and 1 of all other species.

Figure 2. The variability of seed predation within a species across the elevation gradient. The middle line represents the median value of seed mortality. Hinges are the 75th and 25th quartiles. Whiskers extend to the maximum and minimum values and outliers are represented by circles. Species are graphed in order of increasing seed mass.

Figure 3. Seed predation across the elevational gradient. Seed mortality at each elevation is the aggregate seed mortality of all species. Points are fit with a nonparametric regression function using locally weighted scatter plot smoothing. Error bars are binomial confidence intervals. Nelevation=750.

Figure 4. Individual species’ seed mortality over the elevational gradient, plots are ordered by seed mass from top right to bottom left. Nonparametric regressions were fit for each species using locally weighted scatter plot smoothing. Each point represents the number of seeds eaten out of 25 seeds (75 seeds, I. deltoidea, D. lamarkianum, and Z. mays) placed at each elevation. Error bars are binomial confidence intervals.

Figure 5. The relationship between seed mortality and seed mass (g). Seed mortality of each species is the aggregate seed mortality of all elevations. The x axis uses a Log10 scale.

Figure 6. Species seed mortality as a function of the elevational midpoint of genera (m) at each elevation. Points are the seed mortality of a species at the given elevation. Genera that do not occur in the plot network, Zea spp. and Rinorea spp., were not included in this analysis.

Figure 7. Species seed mortality as a function of the elevational midpoint of species (m) at each elevation. Points are the seed mortality of a species at the given elevation. Species that did not occur in the plot network (Table 2) were not included in this analysis.

Figure 8. Seed rain volume from litter traps as a function of elevation (m). (a) Seed rain from February to December (11 months). (b) Seed rain from August to November, the time during which seed predation experiments were installed and censused.

Figure 9. Annual woody biomass increment (T/ha) as a function of elevation (m).

Figure 10. Elevational ranges of rodents and carnivorous mammals and birds in Manu National Park. Derived from mammal census data by Solari et al. (2006) and bird census data from Terborgh (1982) 27

Table 1. Species used in seed predation experiments in order of decreasing seed mass. Volume (mm3) and mass (g) are mean measurements of 10 seeds ± standard deviation.

Species Family Order Mass (g) Volume (mm3) Hesperomeles ferruginea Rosaceae Rosales 0.005 ± 0.002 92.0 ±19.6 Heliocarpus americanus Malvaceae Malvales 0.007 ± 0.003 77.4 ±19.7 Solanum sp. Solanaceae Solanales 0.010 ± 0.009 40.6 ±11.6 Myrica pubescens Myricaceae Fagales 0.013 ± 0.005 74.6 ±27.4 Hyeronima oblonga Euphorbiaceae Malpighiales 0.02 ± 0.01 165.7 ±13.0 Turpinia occidentalis Rosaceae Crossosomatales 0.04 ± 0.02 438.5 ±148.0 Rinorea sp. Violaceae Malpighiales 0.05 ± 0.02 803.1 ±113.3 Guatteria duodesima Annonaceae Magnoliales 0.12 ± 0.06 3920.8 ±813.5 Zea mays Poaceae Poales 0.17 ± 0.02 1305.6 ±256.3 Virola sebifera Fabaceae Magnoliales 0.23 ± 0.11 3947.6 ±430.3 Tapirira guianensis Anacardiaceae Sapinadales 0.29 ± 0.05 6529.7 ±1148.7 Myrcia sp. Myrtaceae Myrtales 0.30 ± 0.08 1829.9 ±473.3 Symplocos psiloclada Symplocaceae Ericales 0.33 ± 0.12 2721.8 ±1102.4 Mollinedia sp. Monimiaceae Laurales 0.35 ± 0.10 3489.5 ±693.2 Ormosia sp. Fabaceae Fabales 0.40 ± 0.06 3254.3 ±535.3 Meliosma vasquezii Sabiaceae Sabiales 0.46 ± 0.04 9343.2 ±924.5 Wettinia sp. Arecaceae Arecales 0.53 ± 0.09 4347.3 ±594.5 Prunus detrita Rosaceae Rosales 0.60 ± 0.11 6299.4 ±1042.4 Guarea pterorhachis Meliaceae Sapinadales 0.60 ± 0.29 7629.3 ±1255.6 Protium sp. Burseraceae Sapindales 0.65 ± 0.11 6021.3 ±1112.0 Matisia malacocalyx Malvaceae Malvales 1.24 ± 0.32 13998.7 ±2343.8 Coussarea ecuadorensis Rubiaceae Gentianales 1.45 ± 0.15 9230.8 ±3170.4 Dictyocaryum lamarckianum Arecaceae Arecales 3.02 ± 0.84 20485.7 ±3012.9 Iriartea deltoidea Arecaceae Arecales 3.56 ± 0.62 21800.6 ±3516.4

Table 2. Elevation midpoints derived from permanent plot records. Species are ordered from low elevation to high elevation. Midpoints were calculated taking into account abundance of each species/genera at each elevation. NAs occur where species or genera did not occur in plots.

midpoint of midpoint of species species elevation genus elevation range (m) range (m) Heliocarpus americanus 471 471 Iriartea deltoidea 1264 1264 Virola sebifera 591 1319 Wettinia sp. na 1367 Matisia malacocalyx na 1379 Guarea pterorhachis na 1388 Coussarea ecuadorensis na 1430 Turpinia occidentalis na 1464 Ormosia sp. na 1500 Dictyocaryum lamarckianum 1579 1579 Protium sp. na 1633 Tapirira guianensis 1546 1659 Guatteria duodesima na 1725 Myrcia sp. na 1741 Mollinedia sp. na 1785 Hyeronima oblonga 1690 1829 Meliosma vasquezii na 2211 Prunus detrita 1718 2683 Solanum sp. na 2835 Hesperomeles ferruginea na 3000 Myrica pubescens 3000 3000 Symplocos psiloclada 3409 3187 Rinorea sp. na na Zea mays na na

Table 3. Dates of installation and censuses of seed predation sites. The number of days from installation are in parentheses.

Plot Installation First Census Second Census Third Census TU 3450 16 Aug 2008 23 Aug 2008 (8) 13 Sep 2008 (28) 24 Oct 2008 (70) TU 3250 17 Aug 2008 25 Aug 2008 (8) 14 Sep 2008 (28) 25 Oct 2008 (70) TU 3000 18 Aug 2008 26 Aug 2008 (8) 15 Sep 2008 (28) 26 Oct 2008 (70) TU 2750 19 Aug 2008 26 Aug 2008 (7) 16 Sep 2008 (28) 27 Oct 2008 (70) TU 2500 20 Aug 2008 26 Aug 2008 (6) 17 Sep 2008 (28) 28 Oct 2008 (70) TU 2250 28 Aug 2008 18 Sep 2008 (21) 25 Sep 2008 (28) 6 Nov 2008 (70) TU 2000 30 Aug 2008 19 Sep 2008 (20) 25 Sep 2008 (26) 8 Nov 2008 (71) TU 1750 31 Aug 2008 20 Sep 2008 (20) 25 Sep 2008 (25) 9 Nov 2008 (71) SP 1750 20 Sep 2008 26 Sep 2008 (6) 28 Oct 2008 (38) 29 Nov 2008 (71) SP 1500 2 Sep 2008 11 Sep 2008 (9) 26 Sep 2008 (24) 11 Nov 2008 (70) TO 1000 30 Aug 2008 14 Sep 2008 (15) 27 Sep 2008 (28) 8 Nov 2008 (71)

Table 4. Summary of Cox proportional hazard regression.

2 source DF χ p elevation 1 438.18 0.00 species 23 52.7 0.0004 species by elevation 23 43.06 0.007 interaction

Table 5. Seed mortality of species aggregated over all elevations and seed mass modeled using a generalized linear model with a quasi-binomial error distribution.

residual coefficient DFresiduals p deviation seed mass -0.08 616.29 22 0.46

Table 6: Linear regressions of seed mortality and the elevational midpoint of genera. At each elevation, the species seed mortality at that elevation was used. Genera that do not occur in the plot network, Zea spp. and Rinorea spp., were not included in this analysis.

2 Std. elevation R DF DFresiduals p Errorresiduals 1000 0.18 1 0.32 20 0.06 1500 0.02 1 0.28 20 0.58 1750 6 x 10-6 1 0.24 20 0.99 1850 0.01 1 0.27 20 0.60 2000 0.01 1 0.31 20 0.66 2250 0.04 1 0.20 20 0.38 2500 0.01 1 0.21 20 0.63 2750 0.002 1 0.22 20 0.85 3000 0.08 1 0.17 20 0.21 3250 0.03 1 0.22 20 0.48 3450 0.17 1 0.22 20 0.06

Table 7. Linear regressions of seed predation on and elevational midpoint of species. At each elevation the species mortality at that elevation was used. Only the 12 species that occurred in the plots (Table 2) were used in this analysis.

2 Std. elevation R DF DFresiduals p Errorresiduals 1000 0.30 1 0.31 10 0.06 1500 0.02 1 0.22 10 0.65 1750 0.01 1 0.25 10 0.78 1850 0.01 1 0.24 10 0.76 2000 0.003 1 0.25 10 0.87 2250 0.03 1 0.20 10 0.59 2500 0.05 1 0.22 10 0.49 2750 3.6 x 10-4 1 0.16 10 0.95 3000 0.18 1 0.18 10 0.17 3250 0.002 1 0.23 10 0.90 3450 0.32 1 0.23 10 0.06

Table 8. Linear regressions of measures of ecosystem productivity vs. elevation.

measure of Std. ecosystem R2 DF DF p Error residuals productivity residuals woody biomass increment 0.6943 1 0.4838 10 0.000762 annual seed volume 0.4086 1 0.5245 9 0.0342 seasonal seed volume 0.2513 1 0.862 9 0.1162

Figure 1 1000 m a) Amazon 1500 m

1 hectare plot 1750 m

1850 m PERU 2000 m

Manu 2250 m National Park 2500 m 2750 m 3000 m 3250 m Andes 3450 m

c) b) C M He Z M SIPr Gu D O D Z He V W TMR My Myr Z S I T I Gua Pr H D 36

Figure 2

Key to Species Abbreviations: Hel = H. amerianus Hes = H. feruginea So = Solanum sp. Myri = M. pubescens Hy = H. oblonga Tu = T. occidentalis Ri = Rinorea sp. Guat = G. duodesima Ze = Z. mays Vi = V. sebifera Ta = T. guianensis Myrc = Myrcia sp. Sy = S. psiloclada seed mortality Mo = Mollinedia sp. Or = Ormosia sp. Me = M. vasquezii We = Wettinia sp. Pru = P. detrita Guar = G. pterorhachis Pro = Protium sp. Ma = M. malacocalyx Co = C. ecuadorensis Di=D. lamarkianum

0.0 0.2 0.4 0.6 0.8 1.0 Ir = I. deltoidea

Hel Hes So Myri Hy Tu Ri Guat Ze Vi Ta Myrc Sy Mo Or Me We Pru Guar Pro Ma Co Di Ir species

Fig. 3

seed mortality seed 0.0 0.2 0.4 0.6 0.8 1.0

1000 1500 2000 2500 3000 3500

elevation (m)

Figure 4

Hesperomeles ferruginea Heliocarpus americanus Solanum sp. Myrica pubescens Hyeronima oblonga Turpinia occidentalis

mortality mortality mortality mortality mortality mortality

0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0 1000 2000 3000 1000 2000 3000 1000 2000 3000 100020003000 1000 2000 3000 1000 2000 3000 elevation (m) elevation (m) elevation (m) elevation (m) elevation (m) elevation (m)

Rinorea sp. Guatteria duodesima Zea mays Virola sebifera Tapirira guianensis Myrcia sp.

mortality mortality mortality mortality mortality mortality

0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0

1000 2000 3000 1000 2000 3000 1000 2000 3000 100020003000 1000 2000 3000 1000 2000 3000 elevation (m) elevation (m) elevation (m) elevation (m) elevation (m) elevation (m)

Symplocos psiloclada Mollinedia sp. Ormosia sp. Meliosma vasquezii Wettinia sp. Prunus detrita

mortality mortality mortality mortality mortality mortality 0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0 1000 2000 3000 1000 2000 3000 1000 2000 3000 100020003000 1000 2000 3000 1000 2000 3000 elevation (m) elevation (m) elevation (m) elevation (m) elevation (m) elevation (m) Guarea pterorhachis Protium sp. Matisia malacocalyx Coussarea ecuadorensis Dictyocarium lamarckianum Iriartea deltoidea

mortality mortality mortality mortality mortality mortality

Figure 5 seed mortality seed 0.6 0.7 0.8 0.9

0.005 0.010 0.020 0.050 0.100 0.200 0.500 1.000 2.000

seed mass (g)

Figure 6

1000 m 1500 m 1750 m 1850 m

seed mortality seed mortality seed mortality seed mortality

0.6 0.7 0.8 0.9 1.0 0.70 0.75 0.80 0.85 0.90 0.95 1.00

0.50.60.70.80.91.0 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1500 2000 2500 3000 1500 2000 2500 3000 1500 2000 2500 3000 1500 2000 2500 3000 elevation midpoint of genus (m) elevation midpoint of genus (m) elevation midpoint of genus (m) elevation midpoint of genus (m)

2000 m 2250 m 2500 m 2750 m

seed mortality seed mortality seed mortality seed mortality

0.4 0.5 0.6 0.7 0.8 0.9 1.0 0.5 0.6 0.7 0.8 0.9 1.0 0.6 0.7 0.8 0.9 1.0 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1500 2000 2500 3000 1500 2000 2500 3000 1500 2000 2500 3000 1500 2000 2500 3000 elevation midpoint of genus (m) elevation midpoint of genus (m) elevation midpoint of genus (m) elevation midpoint of genus (m)

3000 m 3250 m 3450 m

seed mortality seed mortality seed mortality

0.2 0.4 0.6 0.8 0.4 0.5 0.6 0.7 0.8 0.9 0.20.30.40.50.60.70.80.9

1500 2000 2500 3000 1500 2000 2500 3000 1500 2000 2500 3000

elevation midpoint of genus (m) elevation midpoint of genus (m) elevation midpoint of genus (m) 41

Figure 7

1000 m 1500 m 1750 m 1850 m

mortality seed mortality seed mortality seed mortality seed

0.6 0.7 0.8 0.9 1.0 0.70 0.75 0.80 0.85 0.90 0.95 1.00

0.5 0.6 0.7 0.8 0.9 1.0 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 500 1000 1500 2000 2500 3000 3500 500 1000 1500 2000 2500 3000 3500 500 1000 1500 2000 2500 3000 3500 500 1000 1500 2000 2500 3000 3500

elevation midpoint of species (m) elevation midpoint of species (m) elevation midpoint of species (m) elevation midpoint of species (m)

2000 m 2250 m 2500 m 2750 m seed mortality seed seed mortality seed mortality seed mortality seed 0.4 0.5 0.6 0.7 0.8 0.9 1.0 0.50.60.70.80.91.0 0.6 0.7 0.8 0.9 1.0 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 500 1000 1500 2000 2500 3000 3500 500 1000 1500 2000 2500 3000 3500 500 1000 1500 2000 2500 3000 3500 500 1000 1500 2000 2500 3000 3500

elevation midpoint of species (m) elevation midpoint of species (m) elevation midpoint of species (m) elevation midpoint of species (m)

3000 m 3250 m 3450 m seed mortality seed mortality seed mortality seed 0.2 0.4 0.6 0.8 0.4 0.5 0.6 0.7 0.8 0.9 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

500 1000 1500 2000 2500 3000 3500 500 1000 1500 2000 2500 3000 3500 500 1000 1500 2000 2500 3000 3500

elevation midpoint of species (m) elevation midpoint of species (m) elevation midpoint of species (m) 42

Figure 8

(a)

(mm^3) volume seed rain logof

12.5 13.0 13.5 14.0

(b)

volume (mm^3) seed rain log of

11.0 11.5 12.0 12.5 13.0 13.5 14.0

1000 1500 2000 2500 3000 3500

elevation (m)

Figure 9 woody biomass increment (T/ha) woody increment biomass 1.5 2.0 2.5 3.0 3.5 4.0 1000 1500 2000 2500 3000 3500

elevation (m)

Figure 10

rodents

carnivorous birds and mammals

number of species

0 102030405060

0 1000 2000 3000 4000 elevation (m)

CURRICULUM VITAE

Rachel A. Hillyer

Education:

Florida Institute of Technology: Melbourne, Florida Bachelor of Science Degree: Biology, May 2007

Wake Forest University: Winston-Salem, North Carolina Master of Science Degree: Ecology, expected May 2009 Thesis title: Seed predation along an elevational gradient in the Tropical Andes, Peru.

Teaching:

2007 Teaching Assistant. Comparative Physiology. Wake Forest University 2008 Teaching Assistant. Ecology and Evolution. Wake Forest University

Grants:

Sigma Xi Grants-in-Aid of Research (2005) NSF Research Experience for Undergraduates (2005)

Publications:

Hillyer, R., B.G. Valencia, M.B. Bush, M.R. Silman, and M. Steinitz-Kannan. 2009. A 24,700-yr paleolimnological history from the Peruvian Andes. Quaternary Research. 71(1):71-82.