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HABITAT ASSESSMENT FOR A THREATENED MARSUPIAL IN TEMPERATE FOREST OF PATAGONIA

BY

MARIANO ALBERTO RODRIGUEZ-CABAL

A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT

OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE

UNIVERSITY OF FLORIDA

2008

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© 2008 Mariano Alberto Rodriguez Cabal

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To Noelia and to all who nurtured my curiosity and love for nature.

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ACKNOWLEDGMENTS

I thank my supervisory committee (L. C. Branch, K Sieving and E. Bruna) for their

mentoring. I also thank the faculty, staff and grad students at the University of Florida (UF)

Department of Wildlife Ecology and Conservation. I thank Mauricio Failla, Director de Fauna de

la Provincia de Rio Negro, Argentina; Gustavo Iglesias and Claudio Chehebar, Nahuel Huapi

National; Park, and staff of Parque Municipal Llao Llao. Special thanks go to M. Aizen, G.

Amico, N. Barrios, G. Barrios, R. Bunge, J. M. Morales, S. Morgan, A. Martínez, M. Nuñez, E.

Perner, A. Pries, R. Reggio, and N. Tercero-Bucardo for valuable assistance in the field and for

their thoughtful comments and suggestions on previous drafts. Field work was supported by

Wildlife Conservation Society, Scott Neotropical Fund, and the Jennings Scholarship of the UF

Department of Wildlife Ecology and Conservation.

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TABLE OF CONTENTS page

ACKNOWLEDGMENTS ...............................................................................................................4

LIST OF TABLES...........................................................................................................................6

LIST OF FIGURES .........................................................................................................................7

ABSTRACT.....................................................................................................................................8

CHAPTER

1 HABITAT ASSESSMENT FOR MONITOS DEL MONTE ................................................10

Introduction.............................................................................................................................10 Methods ..................................................................................................................................13

Study Area .......................................................................................................................13 Marsupial Presence - Absence.........................................................................................14 Marsupial Abundance......................................................................................................15 Habitat Variables .............................................................................................................15 Data Analysis...................................................................................................................16

Results.....................................................................................................................................19 Marsupial Presence - Absence.........................................................................................19 Marsupial Abundance......................................................................................................20

Discussion...............................................................................................................................21

2 CONSERVATION IMPLICATIONS....................................................................................25

3 CONCLUSION.......................................................................................................................32

APPENDIX

A CORRELATION ANALYSIS ...............................................................................................33

LIST OF REFERENCES...............................................................................................................35

BIOGRAPHICAL SKETCH .........................................................................................................40

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LIST OF TABLES

Table page 1-1 Habitat variables for sites where monitos del monte were present or absent.. ..................25

1-2 Logistic regression models at the 28 study sites.. ..............................................................26

1-3 Regression models constructed at 12 study sites.. .............................................................27

A-1 Correlation coefficients between habitat variables in the presence – absence survey ......33

A-2 Correlation coefficients between habitat variables in the abundance survey. ...................34

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LIST OF FIGURES

Figure page 1-1 Habitat variables at sites where abundances of monito del monte were determined.........28

1-2 Number of monitos del monte vs. the significance predictor variables.............................29

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Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the

Requirements for the Master of Science

HABITAT ASSESSMENT FOR A THREATENED MARSUPIAL IN TEMPERATE FOREST OF PATAGONIA

By

Mariano Alberto Rodriguez-Cabal

May 2008

Chair: Lyn C. Branch Major: Wildlife Ecology and Conservation

Patterns and processes that shape the distribution and abundance of animals depend on the

scale at which they are evaluated. Understanding theses patterns and processes is fundamental

for the study of plant-seed disperser interactions. Most plants that depend on frugivorous

animals for seed dispersal are dispersed by several species of animals and, the majority of animal

dispersers consume the fruit of several plant species. In contrast to the weak mutual dependence

of most plants and their seed dispersers, some mutualisms in the temperate forest of Patagonia

appear to be obligate. The northern portion of the temperate forest harbors a unique plant –

animal interaction in which the seeds of the mistletoe Tristerix corymbosus, a proposed key

species, are dispersed solely by the endemic marsupial Dromiciops gliroides. I developed a set

of habitat models, in which model variables were defined a prior, to test the hypothesis that the

distribution and abundance of monito del monte is associated principally with abundance of

mistletoe in the temperate forest of Patagonia or that, alternatively, habitat structure and/or other

plants determine the distribution and abundance of this marsupial.

Results show that the distribution of monitos del monte at the broad scale was strongly

influenced by bamboo cover. However, at a smaller spatial scale, the abundance of monitos del

monte are explained by the abundance of mistletoe plants and fruits. The lack of dependence

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among fruiting plants and their seed dispersers often is attributed to the high asymmetry in these

interactions and the important influence of habitat features. Conversely, my results showed that

the mistletoe–monito del monte interaction is more symmetric than many other plant–frugivore

interactions. This interaction is characterized by an obligate partnership of the mistletoe with the

marsupial, and a strong relationship between the abundance of monitos del monte and the

abundance of mistletoe.

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CHAPTER 1 HABITAT ASSESSMENT FOR MONITOS DEL MONTE

Introduction

Distribution and abundance of species depends on the distribution and abundance of other

species with which they interact and habitat factors a various scales (Wiens,1989).

Understanding the patterns and processes that shape distribution and abundance is fundamental

for the study of plant-seed disperser interactions and biodiversity conservation. Seed dispersal

plays an important role in creating and maintaining diversity in plant communities (Schupp et al.,

2002). At large scales, appropriate habitat may be the most important factor limiting distribution

and abundance of frugivores (Wiens, 1989). Habitat characteristics such as availability of a

variety of food resources, nest sites, and distance to shelter, influence frugivores distribution and

could be play a critical role in regulating the abundance of these species (Fedriani, 2005). At a

small scale, habitat characteristics in which fruiting plants are surrounded may be more

important (Herrera, 1998). Previous studies have demonstrated that frugivores select plants or

good patches based on habitat features rather than on plant phenotypic traits (Herrera, 1998;

Fedriani, 2005). For example, frugivores could minimize predation risk by selecting sites with

high cover of vegetation to avoid predators during foraging (Howe, 1979). Thus, habitat factors

may limit the degree to which frugivorous animals track their food resource, and human impacts

on habitat of interacting species can have cascading effects.

Seed dispersal mutualisms influence patterns of seedling recruitment, plant demography,

and population persistence, and thus potentially have widespread effects on the rest of the

community (Janzen, 1980; Feinsinger, 1987; Bond, 1994; Levey and Benkman,1999; Herrera,

2002; Spiegel and Nathan, 2007; Rodriguez-Cabal et al., 2007). The majority of plants that

depend on frugivorous animals for seed dispersal are dispersed by several species of animals

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and, most animal dispersers consume the fruit of several plant species (Herrera, 1998; 2002).

Mutual dependence of most plants and seed dispersers is weak, and asymmetry is common.

Asymmetry in plant–animal interactions is represented in terms of the effect of one species on

another species relative to the strength of the reciprocal effect (Vazquez and Aizen, 2004;

Vazquez et al., 2005; Bascompte et al., 2006; Vazquez et al., 2007). Asymmetry is particularly

evident for specialist plants, which tend to interact mostly with generalist animals (Vazquez and

Aizen, 2004; Bascompte et al., 2003; Bascompte et al., 2006). Generalist plants most often

interact with generalist and specialist animals (Vazquez and Aizen, 2004; Bascompte et al.,

2003; Bascompte et al., 2006).

In contrast to the weak mutual dependence of most plants and their seed dispersers, some

mutualisms in the temperate forest of Patagonia appear to be obligate. This system provides an

ideal opportunity to examine whether the distribution and abundance of an animal disperser

depends on the distribution and abundance of a specific fruit. A large proportion of the flora in

this temperate forest depends on mutualistic animals (Armesto et al., 1996; Aizen and Ezcurra,

1998; Aizen et al., 2002). This level of mutualism is one of the highest recorded for a temperate

ecosystem and is comparable to those from tropical forests (Willson et al., 1989; Willson, 1991).

Unlike the mutualism structure in tropical forests, in this temperate forest many species of flora

depend on a few mutualistic animals for their survival (Aizen et al., 2002).

The northern portion of the temperate forest harbors a unique triangle of keystone

mutualists comprised of a hummingbird (Sephanoides sephaniodes), a mistletoe (quintral,

Tristerix corymbosus), and the marsupial (monito del monte, Dromiciops gliroides, Amico and

Aizen, 2000). This hummingbird is responsible for pollinating nearly 20% of the endemic

species of woody flora in this biome (Armesto et al., 1996; Aizen et al., 2002). The mistletoe

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blooms in winter and is the only source of nectar for the hummingbird during that period (Smith-

Ramírez, 1993; Aizen and Ezcurra, 1998). The monito del monte is the only known disperser of

the mistletoe in this temperate forest (Amico and Aizen, 2000). Moreover, the passage of the

seed through the marsupial’s gut is crucial to triggering germination (Amico and Aizen, 2000).

The isolation from other similar biotas since the disruption of Gondwana allowed the evolution

of monito del monte which is the only extant member from the ancient family Microbiotheriidae.

Because of the long evolutionary history of association of monitos del monte and the

mistletoe and the specific fruiting characteristics and distribution of mistletoes in this temperate

forest, I hypothesized that the distribution and abundance of monitos del monte and mistletoe

might be related closely. Mistletoe produces a large crop size every year and is the most

abundant fleshy fruit in the northern temperate forest of Patagonia (Aizen, 2003, Amico et al., in

press). Once mistletoe fruits are ripe, monitos del monte consume almost exclusively mistletoe

fruits (Rodriguez-Cabal et al., 2007). This mistletoe presents an aggregated distribution and,

therefore, may serve as high density resource patches for the monito del monte. Alternatively,

populations of monitos del monte may not track any single plant species as they are known to eat

and disperse seeds of 80% of the flora with fleshy fruit (Amico et al., in press). Because of the

diversity of fruits available, their populations maybe constrained largely by other habitat factors

such as vegetation cover and structural complexity of the habitat that influence nest site

availability, predation risk, and other aspects of their biology. In this study, I developed a set of

habitat models, in which model variables were defined a prior, to examine the hypothesis that the

distribution and abundance of monito del monte is associated principally with abundance of

mistletoe in the temperate forest of Patagonia or that, alternatively, habitat structure and/or other

plants determine the distribution and abundance of this marsupial. Although experiments are

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required to fully determine the degree of mutual dependence between monitos del monte and the

mistletoe, landscape scale studies such as this provide a foundation for understanding

environmental constraints on these relationships.

Methods

Study Area

I conducted my research in Nahuel Huapi National Park (705,000 ha) and Llao-Llao

Municipal Reserve (1226 ha) in northwestern Patagonia. Nahuel Huapi National Park

encompasses a marked west-to-east rainfall gradient caused by the Andes, which form an

effective barrier to westerly air masses coming from the southern Pacific Ocean. The most xeric

forest site in my study, situated at the xeric boundary with the Patagonian steppe (Cerro Otto,

41°12' S, 71°19' W), has a mean annual precipitation of 1200 mm of which only 10.5 % falls

during the growing season. The western limit of my study located in Puerto Blest (41º 01' S, 71º

49' W) is an area of Valdivian rainforest, one of the rainiest places in the Patagonia (mean annual

precipitation, 4000 mm). Llao-Llao Municipal Reserve (41º 08' S, 71º 19' W) has intermediate

rainfall (mean annual precipitation, 1800 mm). Mean January temperature is 15ºC, and mean

July temperature is 3ºC.

The native forest vegetation in the study area belongs to the Subantartic biogeographical

region, which is distinctive from the Neotropical forest of the rest of South America (Cabrera,

1976). The most common trees are evergreen southern beech (Nothofagus dombeyi), a lenga

beech (Nothofagus pumilio) and a conifer (Austrocedrus chilensis). The understory is dominated

by the bamboo (Chusquea culeou) and the shrub (Aristotelia chilensis, here after A. chilensis).

That is the main host of the mistletoe in the study area (Mermoz and Martín, 1986). The two

forest layers are well differentiated with tree canopy reaching up to 40-m height and understory

reaching up to 5-m height.

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I conducted presence–absence surveys of monitos del monte and examined habitat

variables at 16 sites in Nahuel Huapi National Park and 12 sites in the adjacent Llao-Llao

Municipal Reserve. In addition, trapping was conducted at the 12 sites in the Llao-Llao

Municipal Reserve to determine the relationship between abundance of monitos del monte and

abundance of mistletoe. Sites in Nahuel Huapi National Park were chosen randomly to

incorporate the range of habitats found in the study area. Potential sites in the Llao-Llao

Municipal Reserve were stratified by mistletoe density, and four sites were chosen randomly

within each of the following categories: high (>35 reproductive individuals of mistletoe), low

(<20 reproductive individuals), and no mistletoe. Sites were stratified on abundance of mistletoe

because mistletoe has a patchy distribution and a range of all other variables can be found within

each stratum defined by mistletoe density. I conducted most of the field work during the austral

summer (December 2006 –March 2007) because monitos del monte hibernate during winter and

the main fruiting and dispersal season of the mistletoe is summer (Aizen 2003).

Marsupial Presence - Absence

In order to facilitate rapid surveys of presence - absence of monitos del monte, the 28 study

sites were grouped by presence or absence of mistletoe. At sites with mistletoe, I examined all

plants < 15 cm DHB in each site for feces of monitos del monte that contained mistletoe seeds. I

concluded that monitos del monte were present if I found mistletoe seeds dispersed. If no

dispersed seeds were found in the site, I used trapping to determine the presence of monito del

monte. This technique also was used for sites with no mistletoe. Within each site, I placed a 5 x 5

grid (0.25 ha) of Tomahawk-style traps about 10-m apart. Each trap was placed between 1-2 m

above a ground in the shrub closest to the sample point. Traps were baited with apple and

banana. Because the objective was to document presence, once a monito del monte was trapped,

I stopped trapping at this site. Sampling was continued for four nights if no monitos del monte

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were captured. Based on previous capture data for monitos del monte (Rodriguez-Cabal, 2003),

and following procedures in MacKenzie et al. (2002), probability of capture was 99.6% in four

night if monitos del monte were present. I concluded that monitos del monte were absent after

four nights of trapping if no marsupials were captured.

Marsupial Abundance

Abundance of the monito del monte was estimated using multiple capture-recapture

methods with trapping grids as described above. One trapping grid was placed at each of the 12

sites in Llao-Llao Municipal Reserve. Animals were trapped for four periods of four nights each

per site. Traps were checked daily and all trapped marsupials were marked with an individual

code based on ear perforations and released at the point of capture (for more detail see

Rodriguez-Cabal, 2003; Rodriguez-Cabal et al., 2007). Recaptures were noted in subsequent

trapping periods.

Habitat Variables

At each of the 16 sites in Nahuel Huapi National Park, a 5 x 5 grid was established with

points 10 m apart. I measured habitat variables in 5-m radius circular plots centered on every

second point (n = 13 per site). Similar sampling was conducted at sites trapped in Llao-Llao

Municipal Reserve with plots centered on every second trap. I measured the following variables

to represent the biological and physical structure of the habitat: number of reproductive

individuals and crop size of three understory plants that produce fleshy fruits (mistletoe, A.

chilensis, and Azara microphylla), cover and height of bamboo, complexity of habitat structure,

canopy cover, understory cover and the number of the two most common tree species (N.

dombeyi and Austrocedrus chilensis). Reproductive individuals were plants that presented sexual

structures (i.e., flowers or fruits). In addition for mistletoe, I counted the number of non-

reproductive individuals (2-4 years old), seedlings (those presenting the first two true leaves),

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and number of seeds dispersed. To determine crop size of understory plants, I counted the

number of fruits on a subset of three branches dispersed in each crown and then estimated total

crop size by multiplying mean number of fruits per branch by total number of branches in the

crown for each plant. As with mistletoe, seeds of A. chilensis and A. microphylla are dispersed

by monitos del monte, and passage of their seeds through the digestive tract of a monito del

monte increases chance of germination (Amico et al., in press). Cover of bamboo was estimated

visually by summing the total area occupied by bamboo stems and leaves in each plot. Also, I

measured the height of the tallest bamboo stem in each plot. As a measure of habitat complexity

within each plot, I counted the number of contacts with a vertical pole (3-m height) for branches

5 – 10-cm in diameter and oriented < 45° relative to the ground. Good connectivity between

plants in the understory stratum could play a key role in the mobility of this animal, and more

seeds dispersed in monito del monte feces are found on branches with these characteristics

(Amico 2000). Percent cover of the canopy and understory were estimated using a densiometer

at the center of the circular plot. Finally, I counted the total number of the most common trees for

all individuals taller than four meters.

Data Analysis

I used multiple logistic regressions to determine which habitat variables predicted monito

del monte presence-absence at the 28 study sites, and I used multiple regressions to assess the

contribution of habitat variables to explaining abundance of monitos del monte at the 12 study

sites in Llao-Llao Municipal Reserve. Data were log-transformed when necessary to achieve

normality and reduce heteroscedasticity (Table 1-1). For both analyses, I only used explanatory

variables that did not correlate significantly after a Bonferroni correction (Appendix A-1 and A-

2; Tables 1-1, 1-2 and 1-3). I did not used bamboo height and understory cover because these

measures were correlated with bamboo cover and habitat complexity, respectively, and bamboo

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cover and habitat complexity may be more directly related to the biology of monitos del monte,

particular for nest material and mobility. I did not include crop size of A. microphylla in

analyses because this understory plant did not produce fruits during the study.

Seven models were built to identify habitat variables related to presence – absence and

abundance of monitos del monte. Rather than examine all possible models, models were

developed a priori, that focused on mistletoe, other food plants, and habitat structure as key

factors in the distribution and abundance of this marsupial. I examined the following models: (1)

Global -- all habitat variables, (2) Food plants -- number of reproductive individuals of major

food plants that produce fleshy fruits eaten by monitos del monte, (3) Fruit abundance and

bamboo -- crop size of plants with fleshy fruits and cover of bamboo, (4) Mistletoe plants and

bamboo -- number of reproductive mistletoes and bamboo cover, (5) Mistletoe plants, (6)

Bamboo, (7) Habitat structure -- all habitat variables unrelated to food plants (Table 1-2 and 1-

3). Bamboo cover was included as a separate variable because this plant is an important source

of nest material (Jimenez and Rageot 1979), provides connectivity for arboreal movement, and

may inhibit predation by aerial predators. I used an approach that compared the suite of models

using Akaike’s information criteria (AIC), which allows direct comparison of models with

different number of parameters. AIC is calculated for a suite of models and the best fitting one

has the smallest AIC (Burnham and Anderson, 2002; Whittingham et al., 2005). I applied small-

sample version of AIC (AICc), because the ratio of number of observations to number of

parameters was <40. AICc was calculated for each model with the algorithm:

a) AIC = -2 log (L) + 2 K

b) AICc = -2 log (L) + 2 K + (2 K (K + 1))/ (n - K - 1)

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where log (L) is the log-likelihood function evaluated for the maximum likelihood parameter

estimates, K is the number of parameters in the model and n is the number of observations. ∆AIC

represents the difference between the AICc score for each model and the AICc score of the best

model. The absolute value of AIC is unimportant; instead ∆AIC indicates relative support for the

models. ∆AIC values <2 indicate that models are similar. When ∆AIC was <2, I chose the most

parsimonious model as the best model (i.e., the model that used the least number of parameters).

To evaluate goodness-of-fit for the multiple logistic regressions models, I used Nagelkerke

R2. A true R2, which measures the variability in the dependent variable that is explained by a

linear regression models, cannot be calculated for logistic regression models (Hosmer and

Lemeshow, 1989). However, because deviance can be thought of as a measure of how poorly the

model fits (i.e., lack of fit between observed and predicted values), an analogy can be made to

sum of squares residual in ordinary least squares. This pseudo-R2 is designed to have similar

properties to the true R2. The pseudo-R2 is based on comparison of the likelihood of the current

model to the “null” model (one without predictors). A larger pseudo-R2 indicates that more of the

variation is explained by the model. Here, I reported the Nagelkerke R2 which is a modified

version of Cox and Snell R2 that ranges from 0 to 1 (Hosmer and Lemeshow 1989). I evaluated

the importance of significant independent variables in logistic regression using the standardized

regression coefficient β, which is the predicted change in odds for a unit increase in the

corresponding independent variable (Hosmer and Lemeshow, 1989). Values of β <1 correspond

to decreases in the odds with increases in the dependent variable; values >1 correspond to

increases in the odds with increases in the independent variable; and values close to 1 indicate

that unit changes in the independent variable do not affect the dependent variable.

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To evaluate the goodness-of-fit for the multiple regression models for abundance of

monitos del monte, I calculated the R2 of the models. In multiple regressions, I evaluated the

importance of significant independent variables by calculating the standardized regression

coefficient β (Ganas and Robbins, 2005). The standardized regression coefficient β is used to

compare the magnitude of effect of different variables by describing the change in the dependent

variable (in SD units) caused by an increase in one unit (SD) of the independent variable, while

all the other independent variables are held constant.

In addition, I compared habitat variables between sites with and without monitos del monte

and at sites where I measured marsupial abundances using an ANOVA. I performed a Chi-square

test to compare the relationship between the presence of monitos del monte and mistletoe

presence at the 28 sites. For the 12 sites where I measured abundance of monitos del monte, I

report the minimum number alive for all sites to allow comparison among sites (Wilson et al.,

1996). Because of the low number of captures in sites without mistletoe, I could not use other

methods. Finally, I performed a regression analysis to examine the relationship between

abundance of monitos del monte and habitat variables that had significant explanatory power in

the multiple regression models. These analyses were conducted using SAS 9.13 and JMP IN for

Windows Ver. 5.1 (SAS Institute, Inc., Cary, NC).

Results

Marsupial Presence-Absence

Three of the seven multiple logistic regression models received substantial support as the

best predictive models of presence-absence of monitos del monte (Table 1-2). The Global model

perfectly predicted the presence-absence of monitos del monte (i.e., Nagelkerke R2 = 1). The

most parsimonious model (Fruit abundance and bamboo) and the Habitat structure model, which

was not ranked in the best models, also explained considerable variation in presence-absence of

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monitos del monte (Table 1-2). Bamboo cover was the only significant predictor variable in the

top models (Table 1-2). The seventeen sites where I found marsupials had more bamboo cover

than sites without monito del monte (Table 1-1). Monito del monte was recorded 91% of the

sites that had more than 10% bamboo cover and in only 35% of the sites with less than 10%

cover. The presence-absence of mistletoe and monito del monte were not related at the 28 sites

(Chi-square = 2.06, df = 1, P = 0.15). Five of the 17 sites where I recorded presence of monito

del monte did not have mistletoe. Five of the eleven sites where monitos del monte were absent

had reproductive mistletoe plants, but I did not find mistletoe seeds dispersed, seedlings or non-

reproductive mistletoe (2-4 years old). The lack of seeds, seedlings and non-reproductive

individuals indicates that there has not been recruitment at least in the last four years. The other

12 sites had mistletoe seeds dispersed in monito del monte feces and seedlings.

Marsupial Abundance

The estimated minimum number alive of marsupials on study plots ranged between 0 and

45 individuals. At eleven of the 12 sites where I measured abundances, I captured monitos del

monte in the first four nights of trapping, in spite of the high variability in local abundance of

this species. Two regression models were candidates for the best predictive model for abundance

of monitos del monte, although several additional models also explained high amounts of

variation in abundance of these marsupials (Table 1-3). The number of reproductive mistletoe or

crop size of mistletoe were significant variables in five of the seven models. Habitat complexity,

bamboo cover, and crop size of A. chilensis appear as significant variables in models that were

not supported as the best models, but P-values for these variables were lower (Table 1-3).

Marsupial abundance increased when the number of reproductive mistletoe, crop size of

mistletoe and A. chilensis, or habitat complexity increased (see regression coefficients β, Table

1-3). In contrast, the relationship between bamboo cover and monito del monte abundance was

21

negative. At these 12 sites, bamboo cover was lowest where the abundance of mistletoe was

highest, but the over all correlation of these variables is not significant (Figure 1-1, Appendix A-

2). Linear regression analysis of the abundance of monitos del monte and the five significant

variables indicates that abundance of monitos del monte is better explained by number of

reproductive mistletoes and crop size of mistletoe than crop size of A. chilensis or structural

variables of the habitat (Figure 1-2). Abundance of monito del monte also correlated with

abundance of non-reproductive-mistletoe plants (R2 = 0.83; P < 0.0001) and with mistletoe

seedlings (R2 = 0.70; P < 0.001).

Discussion

High asymmetry between fleshy fruit plants and seed dispersers has been emphasized as a

mechanisms limiting coevolution of these plants and seed dispersers (Herrera, 1985; 1993;

Bascompte et al., 2003; Vazquez and Aizen, 2004). Other recent work also suggests that habitat

features constrain these species interactions (Fedriani, 2005). In this study at the scale of the

study area, habitat features played an important role in determining presence of monitos del

monte whereas presence or absence of specific food plants and mistletoe did not have an

appreciable effect. Bamboo cover was the most important habitat feature for the presence of

marsupial populations. Leaves of bamboo have been described as a principal resource for nest

building for this marsupial and because monitos del monte are arboreal, bamboo can increase the

mobility of this marsupial in forest understory where fruits and nests are located (Jimenez and

Rageot, 1979; Mann, 1955). However, presence data alone can overestimate or underestimate the

importance of habitat characteristics, because a species can be present but have very different

abundances in different sites (Royle and Nichols, 2003; Bailey et al., 2004). Although the

distribution of monitos del monte at the broad scale was influenced strongly by bamboo cover,

surveys conducted at Llao-Llao Municipal Reserve did not show a significant association

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between abundance of this marsupial and cover of bamboo, except in one non-competitive model

where bamboo cover was related negatively related to abundance of monitos del monte. This

negative relationship may have occurred because the lowest amount of bamboo was in areas with

the highest amount of mistletoe (Figure 1-1). The general lack of importance of bamboo for

explaining abundance of monitos del monte in Llao-Llao Municipal Reserve could be explained

by the fact that when the minimum requirement for bamboo cover is met, which based on my

results may be about 10%, mistletoe plays a more important role than bamboo in regulating the

number of marsupials the habitat can support.

Numerous studies have addressed the link between fruit abundance and frugivore

abundance but clear examples of a single plant regulating the abundance of seed dispersers are

scarce (Levey, 1988; Herrera, 1998; 2002; Loiselle and Blake, 1991; Jordano, 1994; 2000;

Malizia, 2001; but see Moegenburg and Levey, 2003). My data suggest that the relationship

between the abundance of the monito del monte and mistletoe may be stronger and more

symmetric than in many other plant frugivory systems (Herrera, 1998; Moegenburg and Levey,

2003). Even though the monito del monte consumes and disperses 80% of the flora with fleshy

fruits, a significant correlation occurred at the Llao-Llao Municipal Reserve between the

abundance of monito del monte and the abundance of mistletoe plants and fruits. This

relationship was much stronger than with other fruiting species such as A. chilensis. Sites with

high abundance of mistletoe had from 2 to 5 times more monitos del monte that sites without

mistletoe. The strong correlation between mistletoe abundance and abundance of monito del

monte could occur because mistletoe directly affects the abundance of monitos del monte or

because both species are responding to another habitat variable not measured in this study.

Experiments are needed to resolve this issue. However, other data also support the conclusions of

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the strong link between monitos del monte and mistletoe. Once mistletoe fruits are ripe, monitos

del monte change their diet from generalist to consume mistletoe fruits almost exclusively

(Rodriguez-Cabal et al., 2007).

The distribution and abundance of monitos del monte found in this study may be linked to

different habitat variables operating at different scales. This arboreal marsupial lives mainly in

the understory. At a large scale, the distribution of this marsupial may be limited by bamboo

cover, which increases nest sites and/or nest building material and connectivity to where food is

more abundant above ground. At a smaller spatial scale, the abundance of monitos del monte

tracked abundance of mistletoe. This spatial pattern may result from progressive gathering of

fine-grain foraging information by individuals in those forest sectors with high abundance of

reproductive mistletoe.

One of the most common explanations for lack of coevolution in plant-seed dispersal

interactions is the high level of asymmetry found (Bascompte et al., 2003). Specialized species

will have limited chance for coevolution because they are asymmetrically influenced by their

generalized species (Vazquez et al., 2007). Although the monito del monte could exert strong

selection on reproductive traits of this mistletoe as its only seed disperser in the temperate forest,

there is no evidence to support the coevolution of traits in this interaction. Furthermore, the

evidence points in the other direction, in which most of the relevant features of the mistletoe in

the temperate forest of Patagonia like the green color of the mature fruits, a color associated with

mammalian dispersers (van der Pijl, 1982), is driven only by environmental factors, such as

period of day light and temperatures (Amico, 2007; Amico et al., 2007). In the Chilean shrubland

this mistletoe species has fruits that are yellow when ripe, and birds disperse the seeds (Amico,

2007). As in the Australian mistletoe (Loranthaceae and Viscaceae) and mistletoebird (Dicaeum

24

hirundinaceum) mutualisms (Reid, 1987), the mistletoe-monito del monte interaction is an

ecological association rather than a coevolved interaction.

25

Table 1-1. Means (± SD) of habitat variables and summary ANOVA for comparison of means for sites where monitos del monte were present or absent. Means from raw data are shown. Variables that were log-transformed prior to analysis are indicated by †. Significant P-values are indicated by *.

Mean ± SD

Habitat variables Present (n = 17)

Absent (n = 11) F df P-value

No. reproductive mistletoe† 1.68 ± 1.88 1.09 ± 1.56 0.958 1 0.34Crop size of mistletoe† 610.17 ± 725.25 468.68 ± 927.70 2.263 1 0.15No. of A. chilensis plants† 4.06 ± 4.05 1.35.63 ± 1.60 5.322 1 0.03*Crop size of A. chilensis † 62.11 ± 57.30 47.90 ± 146.57 2.263 1 0.15No. of A. microphylla plants 0.73 ± 1.01 0.69 ± 2.29 0.013 1 0.91Bamboo cover (%)† 24.97 ± 27.50 3.57 ± 8.23 11.625 1 0.002*Bamboo height (m) 3.13 ± 1.57 0.98 ± 1.51 11.234 1 0.003*Habitat complexity 3.44 ± 0.93 2.48 ± 1.36 4.87 1 0.04*Understory cover (%) 55.10 ± 23.39 54.24 ± 36.50 0.006 1 0.94Canopy cover (%)† 54.70 ± 20.60 46.28 ± 35.79 2.87 1 0.10Average number of trees 2.94 ± 2.21 1.12 ± 1.54 5.66 1 0.03*

26

Table 1-2. Summary of the seven logistic regression models constructed to determine which habitat variables predicted presence-absence of monitos del monte at the 28 study sites. Competitive models (∆AIC <2) and the significant variables in each model are shown in bold.

Predicted correct (%)

Models Variables AIC AICc ∆AIC df Nagelkerke

R2 β Absent Present Global 20.124 30.124 0.641 9 1 100 100

All variables Food plants 39.129 40.129 10.646 3 0.28 72.7 82.4

No. of reproductive mistletoe No. of A. chilensis plants 45.37 No. of A. microphylla plants

Fruit abundance and 28.483 29.483 0 3 0.62 81.8 88.2 bamboo Crop size of mistletoe

Crop size of A. chilensis Bamboo cover 13.37

Mistletoe plants and 30.817 31.297 1.814 0.49 72.7 82.4 bamboo No. of reproductive mistletoe

Bamboo cover 11.29 Mistletoe plants 40.502 40.656 11.173 1 0.05 0 100

No. of reproductive mistletoe Bamboo 31.746 31.900 2.417 1 0.40 72.7 82.4

Bamboo cover 8.27 Habitat structure 30.517 32.256 2.773 4 0.62 81.8 88.2

Bamboo cover 10.99 Habitat complexity Canopy cover Average number of trees

27

Table 1-3.Summary of the seven regression models constructed to determine which habitat variables predicted abundances of monito del monte at 12 study sites. Competitive models (AIC <2) and the significant variables in each model are shown in bold. Model variables are the same as in Table 1-2 except for habitat structure. For this analysis, number of N. dombeyi and Austrocedrus chilensis were used instead of average number of trees.

Models Significant variables AIC AICc ∆AIC df R2 β P-value Global 44.623 134.623 86.154 9 0.87 No. of reproductive mistletoe 1.50 <0.0001 Habitat complexity 2.02 0.05Food plants 48.070 51.070 2.600 3 0.80 No. of reproductive mistletoe 0.72 <0.0001Fruit abundance and 48.292 51.292 2.823 3 0.83 bamboo Crop size of mistletoe 0.75 0.0005 Crop size of A. chilensis 0.45 0.04Mistletoe plants and 48.065 49.398 0.929 2 0.83 bamboo No. of reproductive mistletoe 0.95 <0.0001Mistletoe 48.069 48.469 0 1 0.80 No. of reproductive mistletoe 0.89 <0.0001Bamboo 65.311 65.711 17.242 1 0.01 Habitat structure 54.068 64.068 15.599 5 0.67 Bamboo cover -2.02 0.01

28

No. of reproductive mistletoe+

Crop size of mistletoe+

No. A. chilensis plants+

Crop size of A. chilensis+

No. A. microphylla plants

Bamboo cover+

Bamboo height

Habitat complexity

Canopy cover+

Understory cover

No. N. dombeyi

No. A. chilensis

Mea

n an

d S

D

0

10

20

30

40

50

60

70

80

90

100

110

120

130

140

150

160

170

10000

20000

30000 High abundance of mistletoeLow abundance of mistletoeNo-mistletoe

***

**

*

Figure 1-1.Means (± SD) of the habitat variables measured at the 12 sites where abundances of

monito del monte were determined. Means from raw data are shown. Variables log transformed prior to analysis are indicated by +. Significant differences are shown as *** P < 0.0001, ** P < 0.01, * P < 0.05.

29

Bamboo cover (log)

0 1 2 3 40

10

20

30

40

50R2 = 0.01, P = 0.80

No. of reproductive mistletoe (log)

0.0 0.5 1.0 1.5 2.0

No.

mon

itos

del m

onte

0

10

20

30

40

50R2 = 0.80, P < 0.001

Crop size of A. chilensis (log)

0 1 2 3 4 50

10

20

30

40

50R2 = 0.22, P = 0.13

Crop size of mistletoe (log)

0 1 2 3 4 5 6 7 80

10

20

30

40

50R2 = 0.72, P < 0.001

Habitat complexity

0 1 2 3 4 50

10

20

30

40

50R2 = 0.26, P = 0.09

Figure 1-2. Simpler linear regression analysis of the number of monitos del monte vs. the significance predictor variables of the multiple regression models. The coefficient of determination (R2) and P-value are shown.

30

CHAPTER 2 CONSERVATION IMPLICATIONS

The interaction between this mistletoe and its marsupial disperser may have consequences

at the community and ecosystem levels and habitat changes that impact either of these species

could have indirect cascading effects throughout different interaction webs. This mistletoe is

considered a keystone species due to the production of sugar-rich nectar and protein-rich fruits

during periods of food scarcity. This mistletoe also increases mortality of host trees and could

play an important role in plant community diversity. As the only known disperser for the

mistletoe, the monito del monte is important in maintaining these processes. Habitat

fragmentation disrupts the interaction between the mistletoe and monitos del monte (Rodriguez-

Cabal et al., 2007). Fragmentation negatively affects marsupial abundance, fruit removal, seed

dispersal, and seedling recruitment. The local extinction of monitos del monte has been

associated with the complete disruption of mistletoe seed dispersal (Rodriguez-Cabal et al.,

2007). The reason for the local extinction of monitos del monte in fragmented habitats is

unknown. One possible mechanism is reduction of bamboo in fragments results in loss of nest

sites and connectivity. Grazing by cattle and other introduced ungulates significantly alters

habitat structure and composition of the forest, including reduction of bamboo (Veblen et al.,

1992). Effects of grazing are particularly severe in forest fragments where introduced ungulates

have easy access to entire patch.

In this temperate forest, the bamboo blooms and dies at approximately 40-60 years

intervals. Although this is a natural process, the die-off of the bamboo also likely has important

consequences for populations of the monito del monte by reducing nest sites and connectivity.

Loss of bamboo within habitat fragments may have particularly severe consequences because

31

these patches are isolated, reducing the probability of demographic rescue and recolonization

following regeneration of bamboo within the patch.

32

CHAPTER 3 CONCLUSION

In the temperate forest of southern South America, the northern portion (to 41oS) has the

highest biodiversity and number of endemic species, the lowest proportion of protected areas,

and the highest rate of disturbance in this forest (Armesto et al., 1998, Rodriguez-Cabal et al., in

press). The biodiversity of this temperate forest currently is threatened by the highest rates of

destruction, fragmentation, and degradation ever experienced by this system, with more than

120,000 ha of native forest destroyed or degraded annually (Lara et al., 1996).

The alteration of natural habitats through human activities is the principal cause of the

decline and extinction of natural populations (Gaston and Spicer, 2004). Long-term plans to

conserve biodiversity must not only focus in maintaining the elements that form biodiversity but

also on the interactions among these elements (Vazquez and Simberloff, 2003). Understanding

the species and processes that shape ecosystems is fundamental for effective conservation

(Wayne et al., 2006). No previous study has investigated explicitly factors that determine this

austral marsupial’s distribution and abundance or the causes of its present decline. This study

constitutes the first detailed ecological research focused on the identification of the habitat

variables that play the most important role in maintaining the marsupial’s populations. My work

demonstrates that both habitat factors (bamboo) and interacting species (mistletoe) are important

in determining the distribution and abundance of this species.

33

APPENDIX CORRELATION ANALYSIS

Table A-1. Correlation coefficients (r) between habitat variables in the presence-absence survey (n = 28). Significant correlations

after the Bonferroni correction are indicated by * (P < 0.0009).

Crop size of mistletoe

No. of A. chilensis plants

Crop size of A. chilensis

No. of A. microphylla plants

Bamboo cover (%)

No. of reproductive mistletoe 0.89* 0.56 0.15 0.17 -0.19 Crop size of mistletoe 0.50 0.10 0.18 -0.17 No. of A. chilensis plants 0.66* 0.42 0.29 Crop size of A. chilensis 0.10 0.39 No. of A. microphylla plants 0.33 Bamboo cover (%) Bamboo height (m) Habitat complexity Understory cover (%) Canopy cover (%)

Table A-1.

Bamboo height (m)

Habitat complexity

Understory cover (%) Canopy cover (%)

Average no. trees

No. of reproductive mistletoe 0.11 0.29 -0.004 - 0.38 -0.24 Crop size of mistletoe 0.02 0.01 -0.01 - 0.44 -0.28 No. of A. chilensis plants 0.47 0.02 -0.23 -0.07 0.13 Crop size of A. chilensis 0.40 0.19 -0.004 -0.06 0.16 No. of A. microphylla plants 0.36 -0.06 - 0.39 -0.05 0.004 Bamboo cover (%) 0.88* 0.35 -0.11 0.37 0.43 Bamboo height (m) 0.20 -0.29 0.29 0.40 Habitat complexity 0.73* 0.43 0.44 Understory cover (%) 0.23 0.15 Canopy cover (%) 0.88*

34

Table A-2. Correlation coefficients (r) between habitat variables in the abundance survey (n = 12). Significant correlations after the Bonferroni correction are indicated by * (P < 0.0006).

Crop size of

mistletoe No. of A.

chilensis plants Crop size of A.

chilensis No. of A.

microphylla plants Bamboo cover

(%) No. of reproductive mistletoe 0.94* 0.78 0.30 0.09 -0.28 Crop size of mistletoe 0.70 0.16 0.12 -0.13 No. of A. chilensis plants 0.41 0.33 -0.32 Crop size of A. chilensis 0.05 0.46 No. of A. microphylla plants 0.10 Bamboo cover (%) Bamboo height (m) Habitat complexity Understory cover (%) Canopy cover (%) N. dombeyi Table A-2.

Bamboo

height (m) Habitat

complexity Understory cover (%)

Canopy cover (%) N. dombeyi

A. chilensis

No. of reproductive mistletoe 0.33 0.28 0.13 0.21 -0.35 0.46 Crop size of mistletoe 0.39 0.34 0.18 0.28 0.20 0.55 No. of A. chilensis plants 0.63 0.39 0.11 0.56 -0.02 0.53 Crop size of A. chilensis 0.38 0.70 0.67 0.36 -0.14 -0.42 No. of A. microphylla plants 0.32 0.00 -0.23 0.10 0.18 0.09 Bamboo cover (%) 0.65 0.70 0.71 0.68 0.46 -0.26 Bamboo height (m) 0.67 0.50 0.96* 0.33 0.30 Habitat complexity 0.89* 0.58 -0.16 -0.08 Understory cover (%) 0.40 -0.16 -0.35 Canopy cover (%) 0.51 0.27 N. dombeyi 0.17

35

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40

BIOGRAPHICAL SKETCH

Mariano Alberto Rodriguez Cabal was born in Buenos Aires, Argentina in 1976. His

interest in biology began when he very young. Nature has always exhibited a powerful attraction

for him. He studied in a religious high school and obtained a degree in economics. When he

finished his secondary studies, he moved to San Carlos de Bariloche in the foothills of the

Andes, in western Argentina. The magnificent environment around this city, which is within a

national park, led him unequivocally to pursue university studies in biology.

In 1997, he began studying Biology at Universidad Nacional del Comahue. In July 2003,

he graduated as a “Licenciado en Ciencias Biológicas.” Under the guidance of Dr. Marcelo

Aizen and Dr. Andrés Novaro, he conducted his undergraduate thesis research on the effects of

habitat fragmentation on a dispersal mutualism in the temperate forest of southwestern

Argentina. After two years of field work, he completed and defended his thesis, obtaining the

highest grade.

In 2004, he received a Fulbright Scholarship to study abroad. In the next year, he moved

to Florida, USA, where he started his master’s studies at the University of Florida in the

Department of Wildlife Ecology and Conservation. During those years worked under the

supervision of Professor Lyn C. Branch. This work was recognized with three grants. Twice he

earned the Outstanding Academic Achievement Award at UF. In December 2007, he defended

his master’s thesis. He made a firm decision to devote himself to scientific research. He hopes to

continue his doctoral education in the United States of America. On completing his studies, he

will return to his country to contribute to the welfare of his people and the conservation of

Argentina’s biodiversity through teaching and research.