abstract jaime, xavier a. forest understory regeneration after

ABSTRACT

JAIME, XAVIER A. Forest Understory Regeneration after Anthropogenic Disturbances in a

Semi-deciduous Tropical Dry Forest in Puerto Rico. (Under the direction of Stacy A. C.

Nelson, Skip J. Van Bloem and Frank H. Koch).

Human disturbance stimulates changes in the community and canopy structure of

forests and reduces their capacity for resilience. There is limited understanding of how short-

term responses in understory regeneration after fire and bulldozing in dry forests can

influence colonization of pioneer generalist species, non-native invasive grasses or native

vegetation. There is an increasing demand for canopy restoration in dry forest ecosystems to

counter the biotic barriers that invasive vegetation can impose on native trees. The main

objectives of our study were to determine the following: 1) whether human disturbance

modifies the ecosystem of the deciduous dry forest, such that altered soil abiotic conditions

would favor the germination and growth of grasses over woody vegetation in the understory

after disturbances; and 2) with respect to post-disturbance regeneration, whether severe fire

or bulldozing will have distinctive impacts on seasonal seedlings, seedling size classes,

sprouts, species richness and invasion pools within disturbed sites. To answer these

questions, a total of 64 understory sampling subplots (1m2) for five treatments were located

in a mature forest site and a total of 36 subplots for two treatments in a secondary forest site.

Both sites had recently burned due to human activity. Data on soil moisture flux, vegetation

and plant invasion dispersal were collected in the study.

Results showed significant differences in fluctuations of soil moisture because of

seasonal rainfall among treatments in the mature site, but no difference among treatments in

the secondary site. Quicker understory seedling, sprout and species richness regeneration was

revealed in the burn treatment of the secondary site and the bulldozed treatment of the mature

site, while the burn treatment from the mature site had the lowest regeneration during the

year cycle. Recovery and control treatments maintained a stable high concentration of soil

moisture flux, seedling density, sprout density and species richness during the entire year

cycle. The open canopy treatment (Uniola virgata grass) of the mature site showed some

constant establishment of woody species seedlings, with no significant progress in size

classes and significant reduction in species richness during winter 2012, but a substantial

increase in species richness during summer 2013. However, the mature site old-burn

treatment and the secondary site burn treatment displayed strong seedling growth in terms of

both size class and species richness during the year cycle. Results of a post-bulldozing

species colonization study in the mature forest site showed strong dispersal of pioneer

species, both non-native invasive grasses and naturalized generalist trees, from the road into

the forest. These findings provide insight into how time and abiotic conditions in the soil

influence understory regeneration dynamics and invasion after wildfire and bulldozing

disturbances. Even though dry forests are capable of absorbing human activities that mimic

natural disturbances, the frequency and intensity of those disturbances will have major

impacts on the functionality of the system. Anthropogenic disturbances can impact forest

biodiversity and community assemblages by facilitating the intrusion of non-native

vegetation that outcompetes local flora for the open niche. Furthermore, community

assembly dynamics in such dry forest sites demand further long-term research on

community-level interactions between soil nutrient dynamics and plant community response

to such disturbances. This is particularly relevant since an alternative stable stage is

unreachable for this forest type, and the persistent damage caused by such anthropogenic

disturbances could degrade the integrity of the ecosystem to the point of shifting towards

other systems (i.e. chaparral, savanna or grassland).

Forest Understory Regeneration after Anthropogenic Disturbances in a Semi-deciduous

Tropical Dry Forest in Puerto Rico

by

Xavier A. Jaime

A thesis submitted to the Graduate Faculty of

North Carolina State University

in partial fulfillment of the

requirements for the degree of

Master of Science

Forestry

Raleigh, North Carolina

2014

APPROVED BY:

_______________________________ ______________________________

Stacy A. C. Nelson, PhD. Frank H. Koch, PhD

Committee Co-Chair Committee Co-Chair

________________________________

Skip J. Van Bloem, PhD.

Committee Co-Chair

ii

DEDICATION

I would like to dedicate this thesis to my mother, Liana, my father Luis, my brother

Luis Armando, my grandfather Diego Jaime, to my advisers that kept me working hard and

many friends that kept me entertained in my spare time. I am greatly thankful for their moral

support and for everything I learned during this process. I especially feel in debt to those who

always believed in me, even if I didn’t believe in myself, and encouraged me to keep

working hard and never stop following my dreams.

iii

BIOGRAPHY

Xavier A. Jaime Dávila is originally from Humacao, Puerto Rico. He graduated cum

laude from the University of Puerto Rico at Humacao with a Bachelor of Science in General

Biology. During his undergraduate education, he found a special interest in courses such as

community ecology, taxonomy of vascular plants and botany. Those courses nourished his

passion for field research in tropical dry forest ecosystems, and lab work in plant phenology

and evolution. His performance as an undergraduate researcher and field assistant led to a

graduate level interview for a research opportunity in Forestry at North Carolina State

University, which concluded in this thesis. Once his Master’s degree is completed, he plans

to publish the chapters in peer-reviewed journals and continue his career in the ecology field,

with a particular emphasis in invasion ecology.

iv

ACKNOWLEDGEMENTS

First of all, I would like to thank Dr. Denny S. Fernandez Del Viso, Dr. Raymond

Tremblay Laland and Dr. Elvia Melendez-Ackerman for giving me my first scientific

experience in the fields of invasion ecology, ecosystem ecology and evolution. Because of

that opportunity during my undergraduate education, I have been able to gather the essential

tools to become a potential graduate student. In addition, they and Mrs. Emma Suarez

endorsed me for a potential graduate position at North Carolina State University. Special

thanks to Dr. Stacy A. C. Nelson from North Carolina State University for choosing me as

his graduate master’s student in the department of Forestry and Environmental Resources,

and for being able to find the funding from the USDA Forest Service to support my research,

living expenses and course load. Thanks to Dr. Skip J. Van Bloem for being my main

research adviser and for providing me important knowledge and guidance in the process of

studying ecosystem recovery after major disturbances. Special thanks to Dr. Frank Koch for

co-chairing my progress writing the chapters, and for his strong critical thinking in the

process of discussing the work done. I’m thankful for having Tristan Allerton as my field

partner during the brutal first field season and being able to share with him all the ups and

downs that come with the field season. Thank you to all my field technicians/volunteers from

field season II and III, James Rodriguez, Axel J. Acevedo, Luis A. Jaime and Diego Jaime.

Moreover, thanks to my dear pack friends from NCSTATE that became my second family

during this process.

v

TABLE OF CONTENTS

LIST OF TABLES.................................................................................................................vii

LIST OF FIGURES................................................................................................................ix

CHAPTER I

Literature Review........................................................................................................1

CHAPTER II

1.0 Introduction..........................................................................................................11

2.0 Materials and Methods........................................................................................14

2.1 Study sites..................................................................................................14

2.2 Experimental design and measurement of understory regeneration….....16

2.3 Statistical analysis.....................................................................................19

3.0 Results...................................................................................................................20

3.1 Soil abiotic conditions after disturbances………………………………..20

3.2 Woody vegetation coverage regeneration study........................................23

3.3 Native grass coverage regeneration study.................................................26

3.4 Seasonal understory regeneration.............................................................29

3.5 Open canopy vs. closed canopy study: seedling size classes.....................36

4.0 Discussion.............................................................................................................39

4.1 Forest cover regeneration..........................................................................39

4.2 Understory regeneration and species richness..........................................41

4.3 Seedling size class......................................................................................43

5.0 Conclusions...........................................................................................................44

vi

6.0 References...........................................................................................................46

CHAPTER III

Abstract....................................................................................................................56

1.0 Introduction................................................................................................................57

2.0 Materials and Methods..............................................................................................59

2.1 Study site.........................................................................................................59

2.2 Experimental design and measurement of bulldozed trail cross-

transects....................................................................................................60

2.3 Statistical analysis...........................................................................................61

3.0 Results.........................................................................................................................66

3.1 Study of invasive-native grasses and generalist tree species successional

niche colonization after bulldozing disturbance.......................................66

4.0 Discussion...................................................................................................................77

5.0 Conclusions.................................................................................................................78

6.0 References...................................................................................................................79

vii

LIST OF TABLES

CHAPTER II

Table Page

Table 1. Annual accumulation of soil moisture flux (m3/me VWC) from each

treatment following disturbances in Ensenada and Tallaboa-Castle sites as

explanatory variables for seasonality. Superscript letters represent Tukey’s

HSD test for multiple comparison procedure..................................................21

Table 2. Seedling size class (cm height) count during summer 2012 (S-12), winter

2012 (W-12) and summer 2013 (S-13) after disturbances in Ensenada,

Guánica mature site..........................................................................................37

Table 3. Seedling size class (cm height) count during summer 2012 (S-12), winter

2012 (W-12) and summer 2013 (S-13) after disturbances in Tallaboa-Castle,

Guayanilla secondary site................................................................................38

CHAPTER III

Table Page

Table 1. Descriptions and expected direction of a priori occurrence effect model for

invasive grasses from the 555-meter bulldozed cross-transect in the Guánica

Dry Forest reserve section of Ensenada, Guánica. All models are set under

95% confidence interval...................................................................................63

Table 2. Descriptions and expected direction of a priori occurrence effect model for

Uniola virgata and other native grasses from the 555-meter bulldozed cross-

transect in the Guánica Dry Forest reserve section of Ensenada, Guánica. All

models are set under 95% confidence interval.................................................64

Table 3. Descriptions and expected direction of a priori distribution effect model for

Leucaena leucocephala introduced tree species from the 555-meter bulldozed

cross-transect in the Guánica Dry Forest reserve section of Ensenada,

Guánica. All models are set under 95% confidence interval...........................65

viii

Table 4. Statistics for models of M. maximus probability of occurrence derived from

cross-transect surveys conducted along the 555-m bulldozed trail in the

Guánica Dry Forest reserve section of Ensenada. All models are set under

95% confidence interval set. (*) Preferred model.……………………………72

Table 5. Statistics for models of U. virgata probability of occurrence based on cross-

transect surveys conducted along the 555-m bulldozed trail in the Guánica

Dry Forest reserve section of Ensenada. All models are set under 95%

confidence interval set. (*) Preferred model......................................................74

Table 6. Statistics for models of L. leucocephala probability of occurrence based on

cross-transect surveys conducted along the 555- m bulldozed trail in the

Guánica Dry Forest reserve section of Ensenada. All models are set under

95% confidence interval set. (*) Preferred model.............................................76

ix

LIST OF FIGURES

CHAPTER II

Figure Page

Figure 1. Map of study area and treatments in Ensenada mature forest site, Guánica

PR.....................................................................................................................15

Figure 2. Map of study area and treatments in Tallaboa-Castle secondary forest site,

Guayanilla PR…..............................................................................................16

Figure 3. Cumulative concentrations of soil moisture flux (+SD) after disturbances over

time (April-12 to April-13) among all treatments in Ensenada site. P-value

applies to the soil moisture monthly variation.…………................................22

Figure 4. Cumulative concentrations of soil moisture flux (+SD) after disturbances over

time (June-12 to May-13) among all treatments in Tallaboa-Castle site. P-

value applies to the soil moisture monthly variation.……..............................23

Figure 5. Percentage of woody vegetation coverage (±SE) among all treatments in

Ensenada mature site during the year study. P-value applies to the difference

between treatments.………………………………..........................................25

Figure 6. Percentage of woody vegetation coverage (±SE) among all treatments in

Tallaboa-Castle secondary site during the year study. P-value applies to the

difference between treatments.……………….………...................................26

Figure 7. Percentage of Uniola grass coverage (±SE) among all treatments in Ensenada

mature site during the year study. P-value applies to the difference between

treatments.…………………………………………........................................27

Figure 8. Percentage of Uniola grass coverage (±SE) among all treatments in Tallaboa-

Castle secondary site during the year study. P-value applies to the difference

between treatments......................................……………………….…………28

x

Figure 9. Mean seedling regeneration (±SE) among all treatments in Ensenada mature

site during the year study. P-value applies to the difference between

treatments.........................................................................................................30

Figure 10. Mean seedling regeneration (±SE) among all treatments in Tallaboa-Castle

secondary site during the year study. P-value applies to the difference between

treatments.........................................…………………………………………32

Figure 11. Mean sprout regeneration (±SE) among all treatments in Tallaboa-Castle


treatments.........................................………………...……………………….34

Figure 12. Mean species richness density (±SE) among all treatments in Ensenada mature

site during the year study. P-value applies to the difference between

treatments.........................................................................................................35

Figure 13. Mean species richness density (±SE) among all treatments in Tallaboa-Castle


treatments.........................................………………………………….……...36

CHAPTER III

Figure Page

Figure 1. Map of the 555-meter long bulldozed trail (brown line) in Ensenada site with

mature forest stand nature, Guánica PR...........................................................60

Figure 2. Post-bulldozing dispersal pattern of M. maximus, L. leucocephala and U.

virgata along the bulldozed trail during (A) summer 2012, (B) winter 2012

and (C) summer 2013. Note: Locations where none of the three species

occurred were dominated only by sprouting trees other than L. leucocephala.

Gaps presence between distances represent areas dominated only by sprouting

trees..................................................................................................................67

xi

Figure 3. Logistic regression of invasive grasses occurrence model (β0+β1 (Dist_z),

β1< 0) of colonization from road side to bulldoze cross-transect end region at

600 meters range..............................................................................................70

Figure 4. Logistic regression model of native grass occurrence, based only on distance

(β0+β1 (Dist_z), β1>0)....................................................................................73

Figure 5. Logistic regression model of L. leucocephala occurrence, based only on

distance (β0+β1 (Dist_z),

β1<0)................................................................................................................75

1

CHAPTER I

Literature Review

Rates of ecosystem processes are frequently self-regulating with respect to

disturbances and successional changes in ecosystem dynamics, but are sensitive to the

severity, frequency and type of disturbance taking place (Chapin et al, 2002). With respect to

tropical forests, ecosystem restoration often benefits from the addition of positive inputs and

feedbacks between its components that provide full recovery or a new, more stable state for

the disturbed ecosystem (Chapin et al, 2002). Many anthropogenic and natural disturbances

such as soil erosion, wildfire, habitat fragmentation, invasive species introduction and land

degradation must be addressed if restoration practices are to recover natural composition,

structure and processes.

However, regeneration of native communities is highly dependent on resiliency,

species adaptability and composition. The species pool in an ecosystem dictates the

distribution and behavior of plant communities especially where non-native species have

altered fire regimes, creating dispersed and irregular effects on the landscape (Wolfe and Van

Bloem, 2012; D’Antonio and Vitousek, 1992). The interplay between species pool, plant

community structure, canopy, and soil quality determine the response to disturbance and re-

organization of the system, which can buffer changes and maintain crucial functions (Walker

et al, 2004; Folke, 2006). Even if the interaction between resilience and disturbance brings

opportunities of possible recombination of evolved structures and developmental processes in

2

the system (Folke, 2006), the continual occurrence of periodic anthropogenic disturbances

can push the system to a less desirable state where resilience is almost unapproachable.

With respect to ecological resilience, tropical forests represent a major area of focus

because of the increasing frequency of anthropogenic and natural disturbance due to climate

change and human population growth (Thompson et al., 2009; Gunderson, 2000; Molina and

Lugo, 2006). Over 70% of forest fires occur in tropical regions of the globe (Dwyer et al.,

2000; Dwyer et al., 1998), and climate change is expected to increase fire frequency, which

will have ecological and socio-economic repercussions, including for Caribbean ecosystems

(Robbins et al., 2008). Many studies of tropical forests have suggested that fragmentation,

deforestation, land-use change and periodic wildfires limit forest regeneration and ultimately

affect vulnerable species diversity and richness (Molina and Lugo, 2006; Ammondt and

Litton, 2012; Stork et al., 2009). Particularly in the understory succession process in tropical

dry forests, seed banks represent a major source of forest equilibrium from the dry season to

the rainy season (Ceccon et al., 2006), but since wildfires occur mostly in dry season periods,

seed banks can lose viability under extreme heat conditions (Robbins et al., 2008). Indeed, in

similar ecosystem scenarios such as Puerto Rico and Virgin Island’s dry forests, seed bank

viability is too low to drive regeneration under normal circumstances and seedling survival is

almost nonexistent after fire disturbances (Ray and Brown, 1994; Santiago-Garcia et al,

2008).

In recent studies regarding semi-deciduous dry forests and shrub lands in the tropics,

competition between invasive grasses and native vegetation appears to be a major factor

hindering the possibility of equilibrium in the system (J. Rojas-Sandoval et al., 2012). Non-

3

native species invasions in tropical dry forests around the equator have triggered significant

loss of biodiversity, economic problems and disastrous effects in semi-dry forested

ecosystems (Vitousek et al., 1997; Mack et al., 2000; Cabin et al., 2002). Native plant

communities in dry deciduous forests not only suffer niche competition by non-native grasses

(Gallagher et al., 2010), but during the dry season, these invasive grasses also increase fuel

loadings that are sensitive to fire ignition (Robbins et al., 2008; Brandeis and Woodall,

2008). Many initiatives involving reforestation and regeneration of dry deciduous forests that

have undergone fragmentation, wildfire and deforestation, are consistently disrupted by the

resulting synergetic effects of these disturbances, which promote changes in forest ecosystem

structure and microclimates (Cochrane, 2002). When large-scale recovery is constantly

interrupted by the combined effect of disturbances, species interactions and biological

constraints, it is important to consider abiotic parameters such as precipitation patterns when

developing restoration practices since environmental factors (i.e. soil moisture, temperature

and seasonality) can significantly influence plant community structure (Cabin et al., 2002; J.

Rojas-Sandoval et al., 2012).

The concept of alternative stable states as the result of perturbed communities shifting

from their original states is not entirely clear in experimental ecology (Beisner et al., 2003).

Essentially, when disturbances are highly frequent in previously disturbed forests, an

alternative stable state is practically an unreachable goal. For that reason, it is important to

identify the disturbances, the variables affected in the system and those changes that

eventually result in a progressive loss of resiliency (Beisner et al., 2003). The forest’s ability

to maintain resilience depends on tree canopy cover, vegetation vulnerability to hysteresis,

4

understory vegetation regeneration, precipitation-moisture variability, soil dynamics, human

disturbances, species pool and species richness (Hirota et al., 2011). On the perspective of

canopy cover, related studies in secondary subtropical and tropical dry forests, suggest that

tree species with dominant characteristics and that are well-adapted to disturbances (i.e., that

can withstand hysteresis) should be used for restoration purposes, and for natural inhibition

of invasive grass settlement (Lebrija-Trejos et al., 2008; Santiago et al, 2008; Wolfe et al.,

2012).

Since the deforestation of mature and secondary dry forest in Puerto Rico during the

1930's most of the island’s forest cover has been dominated by secondary forests (68%), with

a much smaller proportion (12%) in mature forest (Helmer et al., 2002). However, recent

forest inventories have found that forest cover increased from 364,000 ha to 552,000 ha, and

now comprises 62.2% (20% increase in the last 30 years) of total land cover in Puerto Rico

(Brandeis et al, 2007). In particular, dry forests in the tropics represent less than 42% of all

closed forest types, and only 12% of the live trees in this forest type surpass 10 cm diameter

at breast height or 5 m height, largely because these forests occur on abandoned agricultural

lands or lands clear cut for wood charcoal production in the 1970's (Murphy and Lugo, 1986;

Molina and Lugo, 2006; Wolfe and Van Bloem, 2012). Many of the native trees species are

limited to secondary forest and only 12.5% of the dry forest was left undisturbed, resulting in

the domination of secondary forests with mature forests fragmented into spread out patches

(Brandeis, 2003; Molina and Lugo, 2006). Compared to rainforests, dry forests have the

tendency to recover faster from large-scale natural disturbances such as hurricanes (Van

Bloem et al., 2005). However, continuous anthropogenic disturbances like arson fires are a

5

serious threat to fragile dry forest ecosystems such as in the Guánica Dry Forest Biosphere.

Subtropical semi-deciduous dry forests have slow decomposition of organic matter, low

natural fuel loads and no natural ignition source, which means this system essentially does

not possess a natural fire regime. Since the organic matter present aboveground is rapidly

used by the ecosystem, there is also limited presence of species that promote fire under

natural conditions (Murphy and Lugo 1986; Van Bloem et al. 2004).

High levels of human disturbance stimulate changes in forest composition and reduce

a forest’s capacity for resiliency (Hollings, 1973; Wolfe and Van Bloem, 2012), especially

when there is limited regeneration of native trees; this enables rapid population expansion

and spread of invasive grasses. In fact, dry forests in Puerto Rico are unable to reach an

alternative stable state, which leads to limited feasible solutions for management initiatives in

the implementation of canopy restoration to achieve secondary forests and revert the shift to

savannas or chaparrals caused by grass invasion. Especially when most wildfires are a

resulting feedback between the intrusion of fire-prone and invasive non-native grasses, which

colonize the disturbed areas, increasing fuel loads thereby increase the frequency and

severity of wildfires (Molina and Lugo, 2006; Thaxton et al, 2012).

In order to understand successional processes in post-disturbance regeneration, the

variations in plant community response and invasion need to be evaluated with the

consideration of abiotic factors influencing from both above- and below-ground (i.e. soil

moisture and temperatures). There is experimental evidence which indicates that a single

severe fire can turn an entire forest into chaparral, savanna and eventually grassland in Puerto

Rico, creating a cascade effect on the soil composition and plant community structure in the

6

long run (Litton et al., 2006; Shiels et al, 2008; Wolfe and Van Bloem, 2012). However,

short-term scientific studies need to be performed in order to assess the short-term vegetation

regeneration, as well as the plant community structure and potential invasion response to

wildfire and bulldozing disturbances within treatments in a mature forest site and secondary

forest site. There is a need to evaluate restoration practices for native tree recruitment in the

dry forest, since natural regeneration would not lead to closed canopy cover given a

persistent disturbance regime and grass invasion (Molina and Lugo, 2006; Santiago Garcia et

al, 2008; Ramjohn et al., 2012; Wolfe and Van Bloem, 2012; Garcia-Cancel, 2013).

Management efforts establishing intermediate facilitator pathways by using nursing species

that promote the regeneration process and growth of native tree seedlings in the understory

can be an effective mechanism to achieve regeneration of the ecosystem’s canopy cover. For

example, one tree species, Leucaena leucocephala (Lam.) de Wit, is capable of overcoming

hysteresis of the ecosystem, restoring nitrogen concentrations in soil as an n-fixator and

allocating moisture availability in the soil with its mycorrhizal roots (Parrotta, 2000). Such

species may be able to reverse canopy loss and outcompete the grasses to provide a more

feasible scenario for native tree seedlings to grow after major disturbances (Santiago-Garcia

et al, 2008; Wolfe and Van Bloem, 2012).

The continuous efforts to manage and prevent wildfires in the Guánica Dry Forest

Reserve have been partially successful in restraining the progress of uncontrolled fires from

the road sides to inside the protected forest lands (Canals, 2007). Even though a prescribed

burn initiative has been established among USFS and regional fire fighters since 2003, a

more effective forest management and restoration initiative is needed to control the invasion

7

of grasses and subsequently the wildfires. Nevertheless, before restoration initiatives and

other management actions are initiated, there needs to be better understanding of short-term

regeneration of plant communities in response to anthropogenic disturbances in both mature

and secondary dry forest sites. In particular, there should be detailed analyses of understory

dynamics, in order to clarify patterns of niche colonization by woody species or grasses.

Such analyses should include comparisons of sites and treatment responses, and should

examine the influence of soil abiotic conditions and time.

This thesis was designed to address and provide an understanding of the dynamics

and interactions involved in plant community regeneration in recently and previously

disturbed areas, and the role of soil moisture and temperature in ecosystem biodiversity and

resilience. In detail, this thesis will focus on short-term response of understory regeneration

after wildfires and bulldozing in a protected, mature, semi-deciduous forest stand and after a

wildfire in a previously disturbed secondary forest stand. An additional research objective

was to determine whether plant invasion is occurring after bulldozing disturbance in the

mature forest stand as a result of human activities.

Thesis layout

The thesis is comprised of this introductory chapter and two research chapters that are

projected for publication in peer-reviewed journals. General descriptive information about

the study sites is provided below so that it need not be repeated in each research chapter.

However, the Methods sections of each research chapter expands upon the site explanations

as necessary for each study.

8

Study Sites

The research was conducted in two sites. The first site is in the western section of the

Guánica Commonwealth Dry Forest and Biosphere Reserve near Ensenada, PR

(17°56'59.93" N 66°56'33.83" W elev. 176 ft.), and consists of ~713.69-ha of protected semi-

deciduous tropical dry forest (Ewel and Whitmore, 1973; Wolfe and Van Bloem, 2012). The

soil taxonomy of the site is Fine-loamy, mixed, superactive, isohyperthermic, Typic:

Haplocalcids from the order: Aridisols (Bulldozed entrance comprising 5.3% @ 3.5 acres

with Guayacan clay; 0 to 5% slopes) and Clayey-skeletal, mixed, superactive, nonacid,

isohyperthermic, shallow, Typic: Torriorthents from the order: Entisols (Plot sites comprising

94.7% @ 62.9 acres with Pitahaya-limestone and outcrop-seboruco complex; 40 to 60%

slopes) (USDA Soil survey).

The second site is located on private property in Tallaboa-Castle, Guayanilla, and

consists of ~ 35.69-ha of unprotected semi-deciduous subtropical dry forest, mainly

populated by Fabaceae and Euphorbiaceae shrubs and grasses (18°00'16.03"N 66°45'42.99"

W elev. 154 ft.). Its soil taxonomy is Coarse-loamy, carbonatic, isohyperthermic, aridic,

Typic: Calciustolls from the order: Mollisols (Plot sites comprising 100% @ 8.1 acres with

Aguilita stonyclayloam; 20 to 60% slopes) (USDA Soil survey). Also, the top soil is thin,

alkaline in pH and mostly composed of calcium carbonate and magnesium hydroxide

limestone (USDA, 2008).

Both sites have annual rainfall averaging 860 mm/year (Murphy and Lugo, 1986).

The annual rainfall is primarily distributed in two wet seasons from April-May and August-

November (Murphy and Lugo, 1986), and both sites have an average atmospheric

9

temperature of 25.1°C, which does not vary much throughout the year. The sites are located

~ 20.00 km apart and about 0.15 -1.70 km inland; the second study site is somewhat closer to

the coast than the first site.

Previous wildfires were observed in the Tallaboa-Castle site in the early 1990's,

whereas the Ensenada site had not burned previously except from the west side of the forest

trails (dated back to 2010) in which a 3-year post-burn recovery treatment is located (see

Chapter II). The conditions and nature of those wildfires are highly dependent on the grass

fuel loads (i.e., the amount of fire-prone biomass). The native grass species Uniola virgata

(Poir.) not only represents the most frequently encountered grass species in the ecosystem

under study, but it also tends to form densely clumped colonies in disturbed areas of the

forest with open canopy structure (Monsegur-Rivera, 2009). Additionally, this perennial C4

grass produces a good amount of dead biomass around its base that can represent a potential

source of fire fuel (García-Molinari, 2006). The species’ high germination rate under normal

circumstances, low germination rate after fire and wide distribution across the study sites

makes it useful as a study treatment. The Uniola grass treatment (see Chapter II) is a different

type of control in comparison to the closed canopy forest treatment, as well as a potential

variable to monitor after fire and for future ecosystem regeneration.

Both sites experienced relatively recent fires, Ensenada in March 2012 and Tallaboa-

Castle in April 2012. In addition to these incidents, the Puerto Rico Electric Power Authority

(PREPA) proceeded to bulldoze from the road PR-325 roadside to inside the forest (555.0

meters long by ~ 7.3 meters wide corridor) in the Ensenada site, resulting in further

disturbance. Since the forest is heavily threatened by a variety of invasive grasses across 500

10

– 5000m2 of forest land (Wolfe and Van Bloem, 2012), their percentage of coverage and

occurrence were assessed throughout the disturbed and undisturbed sections of the sites.

11

Chapter II

Case study of Caribbean subtropical semi-deciduous dry forests: Community

assemblage and vegetative understory regeneration after anthropogenic disturbances in

Puerto Rico

1.0 Introduction

Antillean dry forests have experienced high levels of anthropogenic disturbance since

the 16th century in some locations (Ramjohn et al., 2012). More importantly, these disturbed

forests are considered some of the world's hot spots of high endemic population densities of

tropical deciduous trees, but also have a high rate of biodiversity loss due to rapid

deforestation in the19th and early 20th centuries (Maunder et al., 2008; Ramjohn et al.,

2012). Additionally, land use changes are often driven by human activities, triggering

ecosystem alterations that are sometimes exacerbated by external factors like major

economic changes. For example, similar to other parts of the world, a collapse of the

agriculture-based economy promoted extensive land use change in Puerto Rico in the late

1930s, as abandoned agricultural lands experienced reforestation at astonishingly high rates

(Rudel et al., 2000; Brandeis et al., 2007). These sudden land use changes are major drivers

of secondary forest succession, which can have a significant impact on species distributions,

community assemblages and ecosystem functions (Verhoef and Morin, 2010). After the

downfall of agriculture in Puerto Rico (Rivera-Batiz and Santiago, 1996), novel forested

ecosystems became the main pattern of dry forest regeneration. Regardless of the progress

12

made in novel forest regeneration, the closed-canopy cover of these tropical dry forests has

been obstructed by the persistent threat of invasion, competition from shrub species, the

susceptibility of the system to altered fire regimes and additional human-mediated

disturbance (Griscom and Ashton, 2011; Ramjohn et al., 2012).

In tropical dry forests among other ecosystems, wildfires affect plant community

assembly to the extent that decreases in post-fire species richness and populations are often

seen (Hoffmann et al. 2003; Chase, 2003). Fire behavior over landscapes is heterogeneous

and patchy, since the distribution of aboveground biomass fuels and atmospheric conditions

determine the burn patterns (Thaxton et al. 2012; D’Antonio and Vitousek, 1992). As a result

of the historical deforestation that occurred in Puerto Rico during the 17th

through the 19th

centuries with aggressive agricultural practices (Murphy and Lugo, 1986; Franco et al., 1997;

Molina Colón and Lugo, 2006; Griscom and Ashton, 2011; Ramjohn, 2004), much of the

increasing secondary forest regeneration depends on adaptable species composition.

Additionally, land abandonment, land use history and increasing distance from the largest

undisturbed forest patches can have an impact on species richness, but not necessarily on

diversity or community structure (Chinea and Helmer, 2003). Native arboreal species that

are fire-adaptable are typically not found inside dry forests in Puerto Rico (Wolfe, 2008).

Thus, native shrubs and grass communities are capable of quickly colonizing niches left by

the decreasing woody species after frequent fires (Thaxton et al. 2012; Brandeis and

Woodall, 2008). Because of anthropogenic ignitions, vegetative adaptations to fire generally

rely on individuals to survive or regenerate from seed germinations, roots and basal sprouts,

and even resistance to aboveground low- to medium-intensity fires (Otterstrom and

13

Schwartz, 2006). During these types of fires, sprouting provides a much needed benefit to the

plant community, allowing subsistence of the main individual stem to enable post-fire

vegetative establishment. However, with the increasing intrusion of invasive non-native

grasses linked to ignition-prone biomass production, these types of ecosystems experience

constant fire regime alterations due to more intense and persistent fires (Thaxton et al. 2012;

Brooks et al. 2004).

The focus of this study was the quantification of understory vegetative regeneration

components in response to post-fire conditions. Our analyses accounted for differences

between unburned, and previously burned, open-canopy (i.e., grass-covered) and closed-

canopy forest plots by the documentation of short-term fluctuations in understory floristic

regeneration, species composition, and non-native grass invasion into once-burned dry forest

as well as an area of bulldoze disturbance. In order to understand the disturbance effect,

regeneration and resiliency of this system, we focused on the theory that strong species

interactions involved in community structures are either deterministic or historically

contingent (Fukami, 2005). To address these objectives, we examined the following question:

What are the effects that wildfire and bulldoze disturbances have on tropical deciduous dry

forest understory vegetative composition, changes in size class distribution across the

disturbed landscape and species richness within and between forest stands? Our research

hypotheses were as follows: 1) if human disturbance modifies the ecosystem of the

deciduous dry forest then altered soil abiotic conditions among treatment conditions would

favor the germination and growth of grasses over woody vegetation in the understory after

disturbances; and 2) if severe fire and bulldoze determine post-disturbance regeneration in

14

the system, then such disturbances will have distinctive impacts on seasonal seedlings,

seedling size classes, sprouts and species richness pools within disturbed sites.

2.0 Materials and Methods

2.1 Study sites

The research was conducted in two sites. The first site is in the western section of the

Guánica Commonwealth Dry Forest and Biosphere Reserve near Ensenada, PR

(17°56'59.93" N 66°56'33.83" W elev. 176 ft.), and consists of ~713.69-ha of protected semi-

deciduous tropical dry forest (Ewel and Whitmore, 1973; Wolfe and Van Bloem, 2012). The

soil taxonomy of the site is Fine-loamy, mixed, superactive, isohyperthermic, Typic:

Haplocalcids from the order: Aridisols (Bulldozed entrance comprising 5.3% @ 3.5 acres

with Guayacan clay; 0 to 5% slopes) and Clayey-skeletal, mixed, superactive, nonacid,

isohyperthermic, shallow, Typic: Torriorthents from the order: Entisols (Plot sites comprising

94.7% @ 62.9 acres with Pitahaya-limestone and outcrop-seboruco complex; 40 to 60%

slopes) (USDA Soil survey).

The second site is located on private property in Tallaboa-Castle, Guayanilla, and

consists of ~ 35.69-ha of unprotected semi-deciduous subtropical dry forest, mainly

populated by Fabaceae and Euphorbiaceae shrubs and grasses (18°00'16.03"N 66°45'42.99"

W elev. 154 ft.). The site is somewhat closer to the coast than the first study site. Its soil

taxonomy is Coarse-loamy, carbonatic, isohyperthermic, aridic, Typic: Calciustolls from the

order: Mollisols (Plot sites comprising 100% @ 8.1 acres with Aguilita stonyclayloam; 20 to

15

60% slopes) (USDA Soil survey). The top soil is thin, alkaline in pH and mostly composed

of calcium carbonate and magnesium hydroxide limestone (USDA, 2008).

Figure 1: Map of study area and treatments in Ensenada mature forest site, Guánica PR

16

Figure 2: Map of study area and treatments in Tallaboa-Castle secondary forest site,

Guayanilla PR

2.2 Experimental design and measurement of understory regeneration

The conditions in Ensenada’s mature forest site provided the opportunity to develop five

treatments that describe the different scenarios found in the site. The set of treatments is as

follows: 1) Burn - 3.46 acres of the site affected by the wildfire that happened on March 13,

2012, which was caused by a high-voltage power line catching fire after a lightning strike. 2)

Bulldoze – 20 meters long by 6.8 meters wide portion of a bulldozed trail used primarily for

comparison to the Burn treatment in terms of disturbance response. The bulldozed trail was

created by the Puerto Rico Electric Power Authority as a way to move machinery into the

forest to change the burned power line for a new, more efficient power line. This treatment

removed all vegetation as well as 10 cm of top soil. 3) Old-Burn – areas recovering from a

17

wildfire that occurred in 2010. The treatment area is mostly covered by a partially open

canopy structure dominated by shrubs in the understory. 4) Uniola grass open canopy control

treatment dominated by native grasses (i.e. Uniola virgata (Poir.) Griseb) in dense colonies

with trees spread out in areas not colonized by U. virgata and with patches dominated by tree

seedlings in the understory. 5) Forest - closed canopy control treatment that represents the

structure of a common mature forest site in the dry zones of Puerto Rico, dominated by

deciduous trees, matured shrubs and an understory heavily dominated by small woody

seedlings. The Tallaboa-Castle secondary forest site had only two treatments: a recent (April

22, 2012) post-fire scenario, which was labeled as the Castle-Burn treatment, and an

unburned forest control treatment that was labeled as Castle-Forest.

Pre-burn and post-burn understory regeneration were measured with four 1-m2

perpendicular sampling subplots located within a 5.6-m radius circular plot using compass

coordinated locations (1° North, 90° East, 180° South, 270° West). The circular plots were

located within each treatment using a stratified random approach that accounted for the

patchy effect of wildfires in soil, solar irradiation and heterogeneity of the landscape

(Thaxton et al., 2012; Bento-Gonçalves et al., 2012). For the Ensenada mature forest site,

there were six plots in the Burn treatment, three plots in the Old-burn treatment, three plots in

the Forest treatment, three plots in the Uniola grass treatment and four 1 m2 subplots located

in a portion of the Bulldoze trail treatment to maintain consistency with the subplot set-up for

the other treatments. The same sampling approach was employed for the Tallaboa-Castle site,

resulting in six plots in the Castle-Burn treatment and three plots in the Castle-Forest

18

treatment). The total number of understory sampling subplots for repeated measurements in

the Ensenada site was 64, versus 36 subplots in total for the Tallaboa-Castle site.

Grass cover and understory plant community successional behavior was measured by

quantifying the percentage of woody vegetation (trees and shrubs) and native grass coverage

inside the subplots, including any individual that touched a subplot boundary, densities of

emerging seedlings, sprouts (basal, stem or root) and species richness. Emerging seedling

density was determined by their physiological status during summer 2012 survey, winter

2012 survey and summer 2013 survey. All of those seedlings that reached adulthood by

producing inflorescence were disqualified as seedlings and labeled as mature individuals.

Since the majority of shrubs and pioneer species produce inflorescence within a few months,

they were considered mature individuals after the late August-December rainy season and in

summer 2013. We did not apply this same phenology standard for slow-growing hardwood

species, which required height measurement to study the growing process.

We recorded seedling count and composition within the following size classes (Jimu et

al, 2012) : <10cm, 10 – 30 cm, 30 – 50 cm, 50 – 70 cm, and 70 – 90 cm. The size class

distributions provided important information on how seedlings develop, react to biotic and

abiotic conditions present in each treatment and also served as a major component in the

interpretation of seedling mortality and maturity. A survivorship assessment in which

seedlings were monitored during survey seasons and year-round was managed by using

seedling tags (new emerging seedlings were tagged with plastic swizzle sticks color-coded

and documented to keep track of which individuals died, survived or matured). We also

19

measured dry-weight aboveground burned grass fuel biomass in each site and the diameter of

the area burned.

2.3 Statistical analysis

The data on fire consumption of aboveground biomass were used as a percentage index

of fuel load consumption in both the Ensenada and Tallaboa-Castle sites before and after

wildfire. Percentage of vegetation coverage for understory woody and grass vegetative

regeneration among all treatments within each site, between sites burned and forest

treatments, survey periods (summer 2012, winter 2012, and summer 2013) and soil abiotic

conditions were analyzed using two-way ANOVA and Tukey HSD with randomized

incomplete block design (Ensenada block (5 treatments) vs. Tallaboa-Castle (2 treatments)).

Multivariate ANOVA analysis was required for vegetative regeneration per each survey time

(summer 2012, winter 2012, and summer 2013) as categorical values. Vegetation data that

did not met ANOVA assumptions of normality and homogeneity of variance were log10-

transformed (Log10(X+C), C=1) (Howell, 2007; Tabachnick and Fidell, 2007). Shapiro-Wilk

(Royston, 1995) and Kruskal-Wallis (Kruskal and Wallis, 1952) non-parametric tests were

used to compare significance of potential differences found in vegetative maturity and

mortality data that did not have a normal distribution.

Soil moisture (m3/m

3 VWC) and temperature (°C) data were collected as continuous time

series (hourly data from 750 points/mo/probe); averages of all probes per treatment were

subjected to ANOVA analysis to examine vegetation regeneration (percentage of understory

coverage, seedling size classes and seedlings-sprouts-species richness densities) in response

to soil moisture and soil temperature fluxes.

20

3.0 Results

Pre-fire biomass was only collected for the Ensenada site (1.9343 kg/m2 dry weight),

and consisted entirely of Uniola virgata presence. Dry forest species composition between

Ensenada and Tallaboa-Castle were significantly different for species richness distribution (P

= 0.0369) after the fire took place. The percentage of burned grass fuel from the Ensenada

site (89.7%), on 3.46 acres of burned land, was slightly higher than the Tallaboa-Castle site

(86.7%) on 4.40 acres of burned landscape. However, the difference in fire consumption of

woody stem biomass between Ensenada and Tallaboa-Castle was not significantly different

(P = 0.16).

3.1 Soil abiotic conditions after disturbances

Cumulative mean soil moisture (m3/m

3 VWC) among treatments in the Ensenada site

significantly varied (P = 0.00621) during the year cycle (Table 1). The Old-Burn treatment

showed the highest moisture concentration in soil followed by Forest, Burn, Uniola grass and

Bulldoze with the lowest level. Seasonal rainfall and dry season (Figure 3) played an evident

role in soil moisture variation (P = 2.06e-13), showing significant increase in moisture during

the months of August-2012 (highest peak) through December-2012 and the lowest levels in

the dry period from January-2013 to April-2013. However, there was no significant

difference between the Castle-Burn and Castle-Forest treatments in cumulative

concentrations of soil moisture in the Tallaboa-Castle site. In addition, seasonal dry-wet

months (Figure 4) proved to be significantly different (P < 2.0e-16) with high concentration

21

of soil moisture from August-2012 through December-2012 and the lowest concentrations

during January-2013 through May-2013.

Table 1. Annual accumulation of soil moisture flux (m3/m

3 VWC) from each treatment

following disturbances in Ensenada and Tallaboa-Castle sites as explanatory variables for

seasonality. Superscript letters represent Tukey’s HSD test for multiple comparison

procedure.

Treatment Soil moisture flux

(m3/m

3 VWC)

(x̄ ±SD)

Burn 0.143±0.041AF

Bulldoze 0.082±0.021B

Old-Burn 0.186±0.044A

Forest 0.164±0.043AF

Uniola 0.132±0.032F

Castle-Burn 0.118±0.041G

Castle-Forest 0.129±0.045GF

22

Pr (>F) = 2.06e-13

Figure 3: Cumulative concentrations of soil moisture flux (+SD) after disturbances

over time (April-12 to April-13) among all treatments in Ensenada site. P-value

applies to the soil moisture monthly variation.

23

3.2 Woody vegetation coverage regeneration study

The mature forest in Ensenada (Figure 5) and secondary forest in Tallaboa-Castle

(Figure 6) were found to be significantly different (P = 0.0004) based on the percentage of

woody coverage within their respective burn treatments after wildfires. Also, the time effect

was significantly different (P < 0.00001) between the sites. Both sites were found

considerably different (P < 0.00001) between summer 2012 - winter 2012 and between

summer 2012 - summer 2013. Woody vegetation cover in both sites had a seasonal

fluctuation between 20% - 45% coverage in their burn treatments. However, when

evaluating treatment differences in post-disturbance recovery, the percentage of woody

Pr (>F) < 2e-16

Figure 4: Cumulative concentrations of soil moisture flux (+SD) after disturbances

over time (June-12 to May-13) among all treatments in Tallaboa-Castle site. P-

value applies to the soil moisture monthly variation.

24

coverage after wildfire and bulldoze disturbances changed significantly (P = 1.48e-10). The

Forest and the Old-Burn treatments exhibited much higher woody regeneration in the

understory than the Burn and Uniola grass treatments in the Ensenada mature site. These last

two treatments accounted for the lowest overall woody regeneration (below 40%). However,

the bulldoze treatment was not significantly different (P-adj > 0.05) from the other

treatments.

On the other hand, the summer 2012, winter 2012 and summer 2013 survey cycle

shows how rainfall in August-December 2012 played a major role, with winter 2012

displaying an approximately 45% higher rate of regeneration than summer 2012 and slightly

higher than summer 2013. The time effect promoted significant variability in woody

regeneration coverage among (P = 0.0002) all treatments in the Ensenada site. Contrast

analysis for time effect among treatments demonstrated significant variation in woody plant

coverage between summer 2012 – winter 2012 and summer 2012 – summer 2013, with no

significant variation in percentage of woody coverage regeneration during winter 2012 –

summer 2013 (Figure 5).

25

In the Tallaboa-Castle site, variations between forest and burn treatments were highly

significant, with the Castle-Burn treatment exhibiting an average of 40% higher woody

regeneration in the understory than the Castle-Forest control treatment (P = 1.74e-09). Time

effect responded in the same manner with the treatment difference (P = 3.30e-12) showing a

stable seasonal increase in percent of woody coverage in the burn treatment but not the forest

treatment (Figure 6).

-10

0

10

20

30

40

50

60

70

80

90

Burn Bulldoze Old-Burn Uniola Grass Forest

(%

cover

age/

4 m

2/t

reat

men

t)

Treatments from Ensenada mature site

Summer 2012 Winter 2012 Summer 2013

P = 1.48e-10

Figure 5: Percentage of woody vegetation coverage (±SE) among all treatments in

Ensenada mature site during the year study. P-value applies to the difference between

treatments.

26

3.3 Native grass coverage regeneration study

Forest stand comparison of the percentage of native grass coverage demonstrated a

significant difference (P = 0.00221) within the burn treatments between Ensenada (Figure 7)

and Tallaboa-Castle sites (Figure 8). Also, the time effect was significantly different (P<

3.42e-09) between the sites during the study. Among survey seasons, results showed a

significant difference (P-adj<0.0015) between summer 2012 - winter 2012 and (P-

adj<0.00001) between summer 2012 - summer 2013. Seasonal growth exhibited an increase

of an average of 10% during the winter season with some replicates showing outliers in the

30% range of grass regeneration and then, slightly declining to an average of 5% loss during

dry season 2013. When considering all treatments, grass regeneration was found to be

-20

0

20

40

60

80

100

Castle-Burn Castle-Forest

(% c

over

age/

4 m

2/t

reat

men

t)

Treatments from Tallaboa-Castle secondary site


P = 1.74e-09

Figure 6: Percentage of woody vegetation coverage (±SE) among all treatments in

Tallaboa-Castle secondary site during the year study. P-value applies to the difference

between treatments.

27

significantly different (P < 0.00001) among them, with the Uniola grass treatment exhibiting

45% higher average regeneration and an upper level of 65%. Among the other treatments

including the Bulldozed, Burn and Forest treatments, there was no mean significant growth,

with some particular plots representing outliers with 15 to 60% of understory native grass

coverage. However, the Old-Burn treatment exhibited a significant average increase of 15%

with an upper level reaching 20%, which suggests successional progress after the wildfire

that took place two years prior the study. In contrast, seasonality did not represent a

significant influence in the regeneration process of native grasses among treatments in

Ensenada (P-adj > 0.05). Native grass colonization was facilitated by both burning and

bulldozing disturbances.

-20

-10

0

10

20

30

40

50

60

Burn Bulldoze Old-Burn Uniola Grass Forest (% c

over

age/

4 m

2/t

reat

men

t)



Figure 7: Percentage of Uniola grass coverage (±SE) among all treatments in

Ensenada matured site during the year study. P-value applies to the difference

between treatments.

P < 0.00001

28

Time, however, played a significant role (P = 1.97e-06) in native grass extents across

the Castle-Burn treatment in the Tallaboa-Castle site, where grass presence increased from

0% in summer 2012 to an average of 10% in winter 2012 and to 20% in summer 2013. Only

one of the Castle-Forest plots displayed high density of Uniola virgata patches ranging from

35% to 70% presence, while the Castle-Burn treatment showed one outlier with 60% grass

coverage. Despite seasonal soil moisture and temperature, time played an important role (P-

adj < 0.05) in native grass colonization for the Castle-Burn treatment and not for the Castle-

Forest treatment, where a significant difference (P = 0.0042) was observed between dry

season summer 2012 and dry season summer 2013 (Figure 8).

-10

-5

0

5

10

15

20

25

30

Castle-Burn Castle-Forest (% c

over

age/

4 m

2/t

reat

men

t)



P = 0.0042

Figure 8: Percentage of Uniola grass coverage (±SE) among all treatments in Tallaboa-

Castle secondary site during the year study. P-value applies to the difference between

treatments.

29

3.4 Seasonal understory regeneration

Temporal and spatial variations in the understory were assessed by monitoring the

progress of seedlings, sprouts, and species richness with the percentage of vegetative

coverage regeneration and grass regeneration. Multivariate analysis of variance was

conducted on a broader scope to understand the dynamics involved between abiotic

parameters and vegetative succession (seedlings-sprouts-species richness). Significant

temporal variation (P = 0.0019), variation among burn plots (P = 9.89e-06), and soil

temperature flux influence (P = 0.0142) were found for the Ensenada site. When same

procedure was conducted considering all treatments, significant difference (P = 8.89e-13)

was observed among them, while abiotic factors such as soil moisture and temperature fluxes

had an equally significant influence (P = 0.0091) on seedlings-sprouts-species richness

regeneration after disturbance.

30

In more detail, seedling recruitment and colonization in the understory were heavily

dominated by fast-growing pioneers such as Euphorbiaceous shrubs like Corchorus hirsutus,

Croton discolor, Croton rigidus, and Croton glabellus with some relatively fast-colonizing,

Convolvulaceous and Fabaceous plants in the short term under succession. Of all treatments

in Ensenada, the Forest (closed canopy), Uniola grass and Old-Burn treatments shared a

significantly higher density of seedling emergence (P = 1.55e-12) than the two recently

disturbed treatments (Figure 9). The Burn treatment displayed a higher mean seedling

emergence (P = 0.02) during winter 2012 just after the rainy season, while it stayed

0

5

10

15

20

25

30

35

40

45

50


(# s

eedli

ngs/

4 m

2/t

reat

men

t)

Treatments from Ensenada site


Figure 9: Mean seedlings regeneration (±SE) among all treatments in Ensenada


treatments.

P = 1.55e-12

31

particularly low for summer 2012 and 2013. No significant time effect was observed on

seedling emergence among treatments. Soil moisture and temperature fluxes within

treatments reflected significant variation (P = 7.57e-10), with Old-Burn, Uniola grass and

Forest representing the most successful treatments in terms of establishment of seedlings. In

the disturbed treatments, the seedling recruitment process fluctuated with time (significant

growth in summer 2012, higher in winter 2012 and significantly lower mean growth in

summer 2013).

The pattern of seedling emergence in the Tallaboa-Castle site proved that soil

moisture flux played an important role in seedling-sprouts-species richness density variation

(P = 0.004), although soil temperature fluxes did not represent an important aspect of

changes in the Castle-Burn treatment. At the treatment level, neither soil moisture or soil

temperature flux had a significant influence on the burn and forest treatments. The

differences between the Castle-Forest and Castle-Burn treatments demonstrated an evident

higher recruitment activity for the Castle-Burn over the Castle-Forest treatment (P = 0.0002).

The time phenomenon had a slight influence (P = 0.0048) on mean seedling regeneration in

the Castle-Burn treatment as well as between both treatments (P = 0.0002) during the study

(Figure 10). In terms of seasonal temperature flux over the Castle-Burn and Castle-Forest

treatments in the Tallaboa-Castle site, slightly significant changes were observed (P =

0.0023), primarily because of the canopy cover effect in the Castle-Forest treatment lowering

the soil temperature and understory regeneration covering the burned landscape during

32

summer 2013 (showing lower soil temperature [27.26 °C] than the [29.00 °C] in winter

2012).

Basal and root sprout seasonal regeneration were dominated by the intensified

reestablishment of Euphorbiaceous species such as Gymnanthes lucida, Croton discolor,

Croton flavens and Corchorus hirsutus ,as well as Burseraceous (Bursera simaruba),

0

5

10

15

20

25

30

35

40

45

50


(# s

eedli

ngs/

4 m

2/t

reat

men

t)

Treatments from Tallaboa-Castle secondary sites


P = 0.0002

Figure 10: Mean seedling regeneration (±SE) among all treatments in Tallaboa-

Castle secondary site during the year study. P-value applies to the difference

between treatments.

33

Boraginaceous (Bourreria succulenta and Bourreria baccata), Malvaceous (Melochia

tomentosa and Waltheria indica), Rutaceous (Zanthoxylum sp.), Erythroxylaceous

(Erythroxylum sp.) and Rubiaceous (Randia portorricensis) species, among other woody

sprouts. Soil moisture and temperature fluxes and time within treatments in the Ensenada site

did not appear to cause any drastic shift in sprout density regeneration during the study.

The Tallaboa-Castle site, however, showed significant influence (P =0.002) of soil

moisture flux in sprout variation in the Castle-Burn treatment. Soil temperature flux was also

found significant (P = 0.00187) with a decrease in sprout density when reaching a high

temperature of 30.55°C. Time played a significant role in sprout density variation (P = 0.006)

in the Castle-Burn treatment, displaying an increase in sprout density. There was a

difference between treatments (P < 0.00001), as time induced an important vegetative

structural shift (P = 0.001) in which was observed higher sprout density (Figure 11) in the

understory of the Castle-Burn treatment, while such a dynamic was limited in the Castle-

Forest treatment.

34

Seasonal species richness after disturbances in Ensenada showed significant variation

(P = 1.27e-06) in the Burn treatment at the end of the year cycle. With respect to time

influence on species richness, winter 2012 presented a significant (P = 0.0023) increase in

species richness with a slight reduction during the following summer 2013. When soil

moisture and temperature flux parameters were examined, both appeared to have a limited

effect (P = 0.0403) on species richness density on the burn treatment. Time did not explain

significant variation in species richness between treatments. Among all treatments there were

significant differences (P = 5.95e-10), with Bulldoze, Burn, Old-Burn and Forest treatments

reaching an equivalent range of species richness density during winter 2012, while in

-40

-20

0

20

40

60

80

100

120

Castle-Burn Castle-Forest (# s

pro

uts

/4 m

2/t

reat

men

t)



P < 0.00001

Figure 11: Mean sprouts regeneration (±SE) among all treatments in Tallaboa-Castle


treatments.

35

summer 2013 Bulldoze, Old-Burn and Forest treatments shared the highest species richness

density. The Burn treatment showed the lowest recorded density. The Uniola grass and Burn

treatments remained slightly low in species richness during part of winter 2012 and the entire

summer 2013. Soil moisture and temperature flux parameters played a significant role (P =

0.0005) in species richness density variation in the Ensenada site treatments.

At the end of the year cycle in the Tallaboa-Castle site (Table 4), time (P = 0.005) and

soil moisture flux (P = 0.004) significantly influenced the variation in species richness

0

1

2

3

4

5

6

7

8

9


(# s

pec

ies/

4 m

2/t

reat

men

t)



P = 5.95e-10

Figure 12: Mean species richness density (±SE) among all treatments in Ensenada


treatments.

36

density for the Castle-Burn and Castle-Forest treatments alike. According to the post-fire

treatment difference, the burn treatment maintained a slight increase in species richness, but

with different species composition (mostly shrubs and Fabaceae generalist trees) than the

Castle-Forest treatment with its higher population of native trees.

3.5 Open canopy vs. closed canopy study: seedling size classes

Multivariate analysis of variance for the 5 size class distribution for the Burn

treatment in the Ensenada site (Table 1) showed no significant differences, while time (P =

0.000187), soil moisture flux (P = 0.001533) and soil temperature flux (P = 0.00946) had

0

1

2

3

4

5

6

7


(# s

pec

ies/

4 m

2/p

lot)

Treatments from Tallaboa-Castle secondary sites


Figure 13: Mean species richness density (±SE) among all treatments in Tallaboa-

Castle secondary site during the year study. P-value applies to the difference between

treatments.

P = 0.005

37

significant influence on seedling size class distribution. In Tallaboa-Castle (Table 3), a

significant difference (P = 9.95e-07) was found in the Castle-Burn treatment with the same

effect of time (P<0.00001), soil moisture (P<0.00001) and soil temperature fluxes

(P<0.00001) on seedling size class distribution. Between treatments within each site, in

addition to time, soil moisture and soil temperature fluxes, strong significant differences were

found among all treatments in the Ensenada mature site (P <0.00001), as for the Tallaboa-

Castle secondary site with previous abiotic parameters (P <0.0003).

Table 2. Seedling size class (cm height) count during summer 2012 (S-12), winter 2012 (W-

12) and summer 2013 (S-13) after disturbances in Ensenada, Guánica mature forest site.

Size

Classes

S-12

Burn

(x̄ ±SD)

Bulldoze

(x̄ ±SD)

Old-Burn

(x̄ ±SD)

Grass

(x̄ ±SD)

Forest

(x̄ ±SD)

<10 cm 4.8±4.9 5.0±3.5 7.3±6.9 16.4±18.3 29.3±28.7

10-30cm 0.8±1.3 1.8±0.9 11.9±24.1 3.3±4.6 3.6±0.9

30-50cm 0.5±2.2 0.5±1.0 4.1±6.6 1.1±2.4 0.8±0.9

50-70cm 0.0±0.0 0.5±1.0 3.4±2.9 0.3±0.6 0.3±0.5

70-90cm 0.0±0.0 0.0±0.0 0.9±1.2 0.3±0.9 0.6±0.5

W-12 Burn Bulldoze Old-Burn Grass Forest

<10 cm 5.6±4.3 9.8±7.2 11.8±9.4 13.3±12.3 26.8±31.6

10-30cm 2.1±2.1 5.0±3.5 8.8±8.9 10.3±14.6 4.7±2.8

30-50cm 2.0±2.4 0.5±1.0 5.4±8.8 1.8±4.8 1.3±0.9

50-70cm 0.8±1.0 0.0±0.0 2.0±2.8 0.3±0.9 0.3±0.7

70-90cm 0.5±0.8 0.0±0.0 0.1±0.3 0.0±0.0 0.1±0.3

S-13 Burn Bulldoze Old-Burn Grass Forest

<10 cm 3.0±4.3 5.0±2.2 6.3±7.7 22.3±25.5 26.9±34.3

10-30cm 2.0±2.4 5.8±4.6 7.8±7.5 4.2±4.4 2.8±3.2

30-50cm 1.1±1.9 0.5±1.0 8.0±17.9 0.3±1.2 0.9±0.9

50-70cm 0.4±0.7 0.0±0.0 3.2±8.9 0.0±0.0 0.0±0.0

70-90cm 0.1±0.3 0.0±0.0 0.6±2.0 0.0±0.0 0.1±0.3

38

Table 3. Seedling size class (cm height) count during summer 2012 (S-12), winter 2012 (W-

12) and summer 2013 (S-13) after disturbances in Tallaboa-Castle, Guayanilla secondary

forest site.

Size Class

S-12

Burn

(x̄ ±SD)

Forest

(x̄ ±SD)

Size Class

S-13

Burn

(x̄ ±SD)

Forest

(x̄ ±SD)

<10 cm 31.8±30.9 8.3±6.0 <10 cm 8.8±9.9 7.1±6.8

10-30cm 0.3±1.4 6.5±14.7 10-30cm 12.9±20.1 6.4±11.7

30-50cm 0.0±0.0 0.5±0.9 30-50cm 2.9±7.3 0.8±1.1

50-70cm 0.0±0.0 0.2±0.4 50-70cm 0.1±0.6 0.0±0.0

70-90cm 0.0±0.0 0.1±0.3 70-90cm 0.0±0.0 0.0±0.0

Size Class

W-12

Burn

(x̄ ±SD)

Forest

(x̄ ±SD)

<10 cm 11.8±14.3 7.1±6.0

10-30cm 13.2±14.4 7.3±13.2

30-50cm 8.7±8.4 0.8±1.2

50-70cm 3.3±5.0 0.1±0.3

70-90cm 0.8±2.0 0.1±0.3

In Ensenada (Table 2), the Uniola grass, Old-Burn and Forest treatments were

evaluated for seedling-sapling growth based on seedling size class distribution. During

summer 2012, the lowest size class was dominated by the Forest treatment followed by the

Uniola grass treatment. The next size classes (10cm - 30 cm height and 30cm -50cm height)

did not show significant increases in general, with only the Old-Burn treatment having a few

subplots displaying high numbers of seedlings in the intermediate size class. In the bigger

size classes (50cm - 70cm height and 70cm - 90 cm height), the Bulldoze treatment exhibited

the first signs of seedling growth, while Old-Burn had the greatest number of seedlings in

both categories. The Forest treatment exhibited the lowest seedling growth. After winter

2012, the Forest treatment dominated the lowest size class followed by the Uniola grass and

39

Old-Burn treatments. In the 10cm - 30cm size class, the numbers of seedlings were higher in

the Uniola grass and Old-Burn treatments, whereas among disturbed treatments, the Bulldoze

treatment had a slight advantage in seedling presence over the Burn treatment. When

examining the next three bigger classes, Old-Burn dominated the seedling count in size

classes 30cm - 50cm and 50cm - 70cm, while the Burn treatment dominated the largest size

class 70cm - 90cm. In summer 2013, the smallest size class continued to be significantly

represented in the Uniola grass treatment followed closely by the Forest treatment. The next

size class of seedling growth showed a significant increase in seedling density for the Old-

Burn treatment, followed closely by the Bulldoze and Uniola grass treatments.

4.0 Discussion

4.1 Forest cover regeneration

Since few native woody species in Puerto Rican dry forest are fire-resistant or fire-

adapted (Wolfe, 2009), previously disturbed forest patches are susceptible to native and

exotic grass dominance, providing continuous fuel loads that can trigger more wildfires

(Thaxton et al., 2012). However, our fuel load index for both sites did not demonstrate a

difference between them in burned grass biomass as a result of wildfires occurring

spontaneously on separate occasions.

Furthermore, the percentage of woody vegetation and native grass regeneration

coverage after such disturbances proved to be different between the sites and influenced by

time and soil abiotic pressures. The Tallaboa-Castle site showed a higher percentage of

regeneration in both cases (woody vegetation and native grasses) than the Ensenada site.

40

Indeed, the Castle-Burn treatment in the Tallaboa-Castle site showed higher regeneration

density than the homologous Burn treatment as well as the Bulldoze treatment in the

Ensenada site. Nonetheless, it was also found that, beyond abiotic conditions and

disturbances, woody vegetation recolonized the disturbed areas faster than native grasses in

both sites. However, within the Ensenada site treatments it is important to denote that after

three years of regeneration, understory woody coverage (seedlings and saplings) was

reaching forest control levels in the previously burned treatment, whereas in disturbed and

grass treatments the regeneration was much lower at the end of the study. In the Tallaboa-

Castle site, woody regeneration occurred faster in the burn treatment and at a significantly

higher percentage than the control forest understory. These findings show how quickly

species are able to re-establish and colonize disturbed areas between a mature dry forest site

and a secondary dry forest site. Also, native grass coverage was significantly higher in the

Old-burn and Bulldoze treatments near undisturbed grass patches. At the end of the study,

Uniola virgata had colonized the disturbed areas ten times more than the forest plots. In

contrast, the Old-Burn recovery treatment showed essentially the same grass coverage with

minimal variation through time. With respect to the time effect, native grass regeneration in

Ensenada fluctuated depending on seasonal weather, while in Tallaboa-Castle, regeneration

was influenced more by time rather than seasonal wet months. It was also observed that

changes in soil moisture flux, which is an important indicator of groundwater dynamics

(York et al., 2002; Yeh and Eltahir, 2005; Soylu et al., 2014), had significant influence on

woody regeneration but not with native grass regeneration.

41

4.2 Understory regeneration and species richness

Since species are the main point connections of ecological networks and interactions,

many ecological community structures interact in response to abiotic-biotic conditions in a

synergic sequence (Petchey et al, 2010). Previous studies in this system have suggested

significant species recovery and resiliency after 45 years of undisturbed growth, yet not all

forested patches reached the same level of resilience (Molina Colón and Lugo, 2006). A

study based on post-fire vegetation succession in Mediterranean gorse shrublands (De Luis et

al., 2006), in which the authors tested the autosuccessional hypothesis, suggested that

communities dominated by a certain species can exhibit a change in species dominance after

fire. Understanding the severity of fire and its frequency of occurrence (Keeley, 2003;

Keeley et al., 2009) within tropical dry forest or shrubland systems, both systems can be

expected to display the same successional behavior: fast-growing seeder species will exploit

the opportunity that the fire disturbance provides and dominate the landscape, changing the

plant community structure (De Luis et al., 2006; Ojeda et al., 1996).

Our study of understory regeneration and species pools serves as a post-disturbance

survey of possible outcomes in the forthcoming development of the forest stands.

Throughout the seasons, the Old-Burn and Forest plots shared the same species richness

density. Bulldoze disturbance experienced an increase in its species pool, including the

establishment of invasive grasses, which made it the most species-rich (6.8±1.3) treatment at

the end of the study (Table 2). In contrast, the Uniola grass and Burn treatments carried the

lowest species richness throughout the study. In the Tallaboa-Castle site, burn (4.4±1.4) and

forest (4.5±1.4) treatments maintained equivalent species richness consistently throughout

42

the study with no significant changes per season (Table 3). In fact, our results showed that

the Ensenada site (protected mature forest nature prior to disturbances) had a larger species

pool than the Tallaboa-Castle site (unprotected secondary forest nature prior to disturbances).

Moreover, Ensenada’s seedling recruitment among burned and bulldozed treatments

displayed similar variation of gain and loss throughout the seasons, which suggests no

difference between these types of disturbance in terms of seasonal variation of seedling

density. Considering all five treatments, the Old-Burn, Forest and Uniola grass proved to be

similar among them in seedling density as well as with the Bulldoze disturbance treatment,

yet the Burn treatment had the lowest seedling density in general. Overall, the results suggest

that fire represented a more challenging disturbance for seedling establishment during the

successional process than the Bulldoze disturbance.

Sprout density only showed a slight difference between Old-Burn and Burn

treatments, whereas there were no differences among the other treatments. This evidence

suggests the recovery process from wildfires in the understory takes more time than recovery

from bulldoze disturbance. In addition, time, soil moisture and soil temperature fluxes were

pressure factors for seedling regeneration in disturbed treatments rather than in undisturbed

treatments. Canopy cover had a large influence on soil temperature and moisture fluctuations

and their impact on seedling establishment in disturbed areas in comparison to the forested

areas. However, in the Tallaboa-Castle site, the soil moisture and temperature did not show

an influence on seedling recruitment in disturbed areas in comparison to the forested areas.

Possible explanations for these differences between sites might depend on other factors such

43

as precipitation, evapotranspiration in exposed soil after disturbances and canopy structure

between the forested areas in each site.

4.3 Seedling size class

Guánica’s tropical dry forest, among other homologous dry forests, represents one of

the most endangered ecosystems in the tropics (Stoner and Azofeifa, 2009), which depends

greatly on understory resilience and recovery after major disturbances from human activities

resulting in habitat fragmentation. Disturbances are complex events that, depending on the

ecosystem and its species in the understory (Buma and Wessman, 2012), can have significant

impact on seedling growth and survival. Size class distribution with diameter and height

measurements of structural groups proved to be useful in understanding interspecific and/or

intraspecific interactions between trees within stands (Jimu et al., 2012). Although the

diameter at ground height did not represent a significant measurement with respect to post-

disturbance seedling establishment, seasonal height measurement of tagged seedlings

throughout the treatments provided significant evidence about how seedling development

varied seasonally. Seedling size classes between the sites’ analog treatments showed stronger

seedling growth overall in the Tallaboa-Castle burn treatment than Burn and Bulldoze

treatments in Ensenada. The conditions in the Tallaboa-Castle site landscape were

substantially more eroded and exposed than the Ensenada site, and even the soil moisture

flux was lower in Tallaboa-Castle than Ensenada. However, the Tallaboa-Castle secondary

site proved to be more active in the regeneration and growth of seedlings and sprouts than the

Ensenada site, although the Ensenada disturbed treatments showed higher species richness.

44

These findings provide an interesting perspective on mature versus secondary site post-

disturbance vegetation dynamics. According to Chinea and Helmer (2003), secondary forest

can be impacted in species richness after land use change or disturbance (as in this study),

but not necessarily in species composition of the forest. We observed strong input of

generalist Fabaceae trees, Euphorbiaceae shrubs and grasses from unburned areas in the

vicinity of the secondary forest region that was burned. Both the Ensenada and Tallaboa-

Castle sites are examples of tropical dry forest systems with resilient vegetation that can

respond quickly to disturbances (Van Bloem et al, 2007), but the community dynamics may

be influenced more by the site exposure to seed rain and intrusion of opportunist vegetation

that does not contribute to the local species richness.

Potential questions may arise regarding the seedling size class seasonal variations and

their implications for future management strategies and forest resilience. Our seedling

maturity and mortality density study provides important knowledge about those seasonal

variations. According to this study, seedling maturity and mortality through time seems to

conform to expectations for this dry forest succession.

5.0 Conclusion

Historically, the protected forests in the western region of Guánica’s dry forest

biosphere have been composed of large sections of open forest stands, and reduced, heavily

fragmented closed forest stands, in which a small number of large fragments represent most

of the closed forest areas (Ramjohn et al., 2012), including the Ensenada site. Despite the

different influence that large or small forest patches can have on biodiversity and species

45

composition (Murphy et al., 1995; Laurance et al., 2011; Ramjohn et al., 2012), periodic

anthropogenic disturbances can disrupt the process of regeneration and regrowth of forest

stands. Theoretically, regenerating forest stands should be resilient enough and follow the

historically contingent community assemblage regardless of environmental conditions.

However, this study was set for the purpose of examining short-term recovery and understory

regeneration after disturbance which makes it difficult to determine if either a historical

contingency or deterministic assembly scenario happens in the system in just a year cycle

(Fukami, 2010). Nevertheless, the questions answered in the study provide a first insight of

post-disturbance secondary succession. In fact, with available nutrient resources, open

landscape, limited interspecific interaction and invasion, it seems more likely to observe a

historically contingent case scenario occurring in the system studied (Fukami, 2010). Since

community assembly begins with a disturbance, it will require future monitoring of the

system to evaluate if one or the other scenario applies. Additionally, patch size or

aggregation of forest patches, rates of population density and dispersal of native tree species

or invasive species into these forests can be signs of deterministic assembly in the future. The

major concern is the need for more native trees species dispersal from the undisturbed

patches of the forest adjacent to the disturbed areas, which could be difficult to achieve if

environmental or external conditions change the immigration history.

46

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56

Chapter III

Spread of a native grass Uniola virgata, an invasive grass Megathyrsus maximus and a

generalist tree Leucaena leucocephala along a bulldozed trail through subtropical semi-

deciduous dry forest.

Abstract

Tropical deciduous dry forests are among the most threatened terrestrial ecosystems

in the world. There is an increasing demand for canopy restoration in dry forest ecosystems

impacted by anthropogenic disturbances that can counter the biotic barriers exerted by

invasive vegetation on native tree development. A key question is the comparative speed at

which a non-native invasive grass (Megathyrsus maximus), naturalized generalist tree

(Leucaena leucocephala) and native grass (Uniola virgata) can colonize a disturbed (i.e.,

bulldozed and burned) tract of dry forest. The main objective of this study was to determine

whether bulldozing disturbance facilitates plant invasion that alters post-disturbance natural

regeneration of the system, or if the forest’s natural resilience provides resistance to those

biotic pressures.

Results of a post-bulldozing species colonization study in a mature dry forest site

showed strong dispersal of pioneer species, both non-native invasive grasses and naturalized

generalist trees, from the road (i.e. the starting point of the bulldozed path) into the forest.

These findings provide insight into how time influences understory regeneration dynamics

and invasion after wildfire and bulldozing disturbances. Even though dry forests are capable

of absorbing human activities that mimic natural disturbances, the frequency and intensity of

those disturbances will have major impacts on the functionality of the system. Anthropogenic

57

disturbances can impact forest biodiversity and community assemblages by facilitating the

intrusion of non-native vegetation that outcompetes local flora for the open niche.

Furthermore, community assembly dynamics in such dry forest sites demand further long-

term research on community-level interactions between soil nutrient dynamics and plant

community response to such disturbances. This is particularly relevant since an alternative

stable state is unreachable for this forest type, and the persistent damage caused by such

anthropogenic disturbances could degrade the integrity of the ecosystem to the point of

shifting towards less favorable systems (i.e. chaparral, savanna or grassland).

Keywords

Tropical Dry Forest · Grass invasions · Tree invasions · Anthropogenic disturbances ·

Occurrence probability · Plant community interactions · Understory regeneration

1.0 Introduction

An important goal of invasion ecology is to understand how biological invasions are

driven by anthropogenic alterations of native habitats (Vitousek et al., 1996; Wilcove et al.,

1998; Mack, 2003; Lockwood et al., 2007; Gooden and French, 2014). Anthropogenic

disturbances such as fires and bulldozing represent complex deterministic processes,

involving an extensive combination of factors such as species competition for available

resources, changes to ecosystem integrity that can shift community assemblages during

regeneration and environmental constraints that influence above- and belowground

dynamics. These deterministic processes can contribute to the propagation of invasive

58

species in the short-term, but if further disturbances are minimal, the spread of an invader

within an affected ecosystem may ultimately decline over the long term (Rew and Johnson,

2010). On the other hand, given our limited information about overlapping effects of niche

alteration and plant invasion on native communities (Didham et al., 2007; Gooden and

French, 2014), it is difficult to ascertain whether drivers of habitat modification might

interact in such a way as to further facilitate invasions during post-disturbance recovery in

the system (Didham et al., 2007).

In tropical dry forest systems, grass invasion and other habitat modifications driven

by anthropogenic disturbances can yield widely disparate outcomes depending on the degree

of degradation and frequency of perturbation. Since tropical dry forests are among the most

threatened ecosystems in the world (Janzen, 1988; Mooney et al., 1995; Molina and Lugo,

2006), ecological restoration and natural regeneration after disturbances represent primary

management goals for forest resilience and functionality (Griscom and Ashton, 2011). For

instance, in cases where the invasive species of interest are highly fire-prone grasses that

increase the frequency and intensity of wildfires in invaded dry forests, management

recommendations typically focus on controlling fuel loads with prescribed fires in

combination with a restoration of tree canopy cover (Thaxton et al., 2012). However, by

contributing to the spread of invasive grasses (Chinea 2002), additional disturbances such as

bulldozing may further exacerbate the threat of wildfire in dry forests.

Understanding the movement of dominant plant species after such disturbances is therefore

an important component of dry forest management. In Puerto Rico, there is a need to

visualize the distribution and movement of a native grass, Uniola virgata, and a naturalized

59

legume tree, Leucaena leucocephala, that each may be useful in promoting the regeneration

of native tree species and contrast their dispersal patterns with a fire-prone invasive grass,

Megathyrsus maximus, after recent disturbance.

The focus of the study was to examine the spread of these three species after a 7-m

wide track was bulldozed through a mature, native-dominated dry forest in the western

section of Guánica Commonwealth Forest (Puerto Rico). The aim of the study was to

determine whether or not invasion was occurring because of bulldozing, and if so, at what

rate, in order to understand how environmental and biological interactions affect each

species’ distribution throughout the disturbed area and inside the mature forest

2.0 Materials and Methods

2.1 Study site

The sites for this study were located near road PR-325 (~13- 69 meters above sea

level) in the Ensenada sector of Guánica Commonwealth Forest – a ~714-ha section of semi-

deciduous dry forest (Figure 1). Annual rainfall in Ensenada averages 860 mm/yr and is

highly seasonal with 6 dry months (December-March and June-July) split by two wet seasons

from April to May and August to November (Murphy and Lugo, 1986). Atmospheric

temperature averages 25.1°C with low variation annually.

60

Figure 1: Map of the 555-meter long bulldozed trail (brown line) in Ensenada site with

mature forest stand nature, Guánica PR

2.2 Experimental design and measurement of bulldozed trail cross-transects

A 555-m long x 7.3-m wide (on average) bulldozer trail was created by the Puerto

Rico Electric Power Authority in an attempt to extinguish a fire created by a downed high-

voltage power line inside the forest. The bulldozed trail begins at the roadside entrance on

PR-325 and ends 5 meters past the high voltage power-line that triggered the wildfire. The

trail has an uphill gradient. The first 401 m are through mature dry forest; the latter portion of

61

the trail crosses over mature forest (154 m) areas that had burned. Megathyrsus maximus had

already been established along the edge of PR-325 when the trail was created. The burned

area had been a mix of native tree species with a discontinuous canopy and U. virgata. A few

mature L. leucocephala were established in scattered locations within the mature forest. We

established transect lines across the trail at 15-m intervals (n=38). For each transect line, we

identified the species of sprouts or seedlings present at intercept points located every 20-cm

along the line.

2.3 Statistical analysis

To model the relationship between regeneration and invasion, we developed logistic

regression models under binary history of detection (detected = 1, not detected = 0) for each

species, whether there is any species interaction occurring among those species under study

in the bulldoze trail. . Each dependent variable was tested against a particular independent

variable or set of interacting variables that were considered to have a possible impact on

species distribution. This analysis produced a total of 7 models each for the two grasses, M.

maximus (Table 1) and U. virgata (Table 2), and 9 models for the generalist tree l.

leucocephala (Table 3). In all three cases, the set of models included a null model with zero

effect of covariates. For the analysis, we used the statistical software R-Gui 3.0.0 (R

Development Core Team, 2012).

We developed models, via logistic regression, that estimated the probability of

occurrence of M. maximus (Table 1), U. virgata (Table 2) and l. leucocephala (Table 3)

based on distance along the 555-m bulldozed trail. The models were intended to depict the

62

spread of each species from its presumed point of origin at either end of the trail; for the

invasive grass M. maximus and the naturalized tree species L. leucocephala, we measured

distance from PR-325 (i.e. the start of the bulldozed trail), while for the native grass U.

virgata, we measured distance from the trail’s end in the area of burned forest. Distance

from road (Quadratic effect) was designed to address the projected future movement of the

species after the year of study, seasons involved in the survey periods which represent

periods of ending dry months (Summer 2012), precipitation months (Winter 2012), and

ending in dry months cycle (Summer 2013). The parameter of time takes into account the

sampling periods without the influence of seasonality. The fire region parameter interacting

in 154 m of the bulldozed trail addressed the possible influence of fire and bulldozing

disturbances on species distribution.

63

Table 1. Descriptions and expected direction of a priori occurrence effect model for invasive

grasses from the 555-meter bulldozed cross-transect in the Guánica Dry Forest reserve

section of Ensenada, Guánica. All models are set under 95% confidence interval.

Hypothesis Model Structure of model Expected results

No detection or abiotic

influence

p (.) β0 -

Negative influence of trail

distance from roads

(Dist_z) β0+β1 (Dist_z) β1< 0

Positive influence of

distance quadratic effect

(Dist_z)2

β0+β1 (Dist_z)+ β2

(Dist_z)2

β1< 0, β2> 0

Negative influence of

distance and time

(Sea) β0+β1 (Dist_z)+ β2 (Sea-

S1)+ β3 (Sea-W)+ β4

(Sea-S2)

β1< 0, β2< 0, β3≤

0, β4≤ 0


distance and wet season

(Wet) β0+β1 (Dist_z)+ β2 (Wet) β1< 0, β2≤ 0


native grass presence

(NatG)

β0+ β1 (NatG) β1< 0

Negative influence of fire

region and time

(Fire) β0+ β1 (Fire) + β2 (Sea-

S1)+ β3 (Sea-W)+ β4

(Sea-S2)

β1< 0, β2< 0, β3≤

0, β4≤ 0

64

Table 2. Descriptions and expected direction of a priori occurrence effect model for Uniola

virgata and other native grasses from the 555-meter bulldozed cross-transect in the Guánica

Dry Forest reserve section of Ensenada, Guánica. All models are set under 95% confidence

interval.



influence

p (.) β0 -

Positive influence of trail

distance from roads

(Dist_z) β0+β1 (Dist_z) β1> 0



(Dist_z)2

β0+β1 (Dist_z)+ β2

(Dist_z)2

β1> 0, β2< 0


distance and time


S1)+ β3 (Sea-W)+ β4

(Sea-S2)

β1> 0, β2< 0, β3≤

0, β4≤ 0



(Wet) β0+β1 (Dist_z)+ β2 (Wet) β1> 0, β2> 0


invasive grass presence

(InvG)

β0+ β1 (InvG) β1≤ 0

Positive influence of fire

region and time

(Fire) β0+ β1 (Fire) + β2 (Sea-

S1)+ β3 (Sea-W)+ β4

(Sea-S2)

β1> 0, β2< 0, β3≤

0, β4≤ 0

65

Table 3. Descriptions and expected direction of a priori distribution effect model for

Leucaena leucocephala introduced tree species from the 555-meter bulldozed cross-transect

in the Guánica Dry Forest reserve section of Ensenada, Guánica. All models are set under

95% confidence interval.



influence

p (.) β0 -

Negative influence of trail

distance from roads

(Dist_z) β0+β1 (Dist_z) β1< 0



(Dist_z)2

β0+β1 (Dist_z)+ β2 (Dist_z)2

β1< 0, β2> 0


distance and time


S1)+ β3 (Sea-W)+ β4 (Sea-

S2)

β1< 0, β2< 0, β3≥

0, β4≤ 0


distance and dry season

(Dry) β0+β1 (Dist_z)+ β2 (Dry) β1< 0, β2< 0



(Wet) β0+β1 (Dist_z)+ β2 (Wet) β1> 0, β2> 0


invasive grasses presence

(InvG)

β0+ β1 (InvG) β1> 0


native grasses

(NatG) β0 + β1 (NatG) β1< 0

Negative influence of fire

region and time

(Fire) β0+ β1 (Fire) + β2 (Sea-S1)+

β3 (Sea-W)+ β4 (Sea-S2)

β1< 0, β2< 0, β3≥

0, β4≤ 0

66

3.0 Results

3.1 Study of invasive-native grasses and generalist tree species successional niche

colonization after bulldozing disturbance

Species establishment along the bulldozed trail in the Ensenada dry forest site showed

intense colonization of the non-native invasive grass M. maximus and the pioneer naturalized

tree L. leucocephala from the bulldozer entrance (0 m) to 255 m in patches and individuals

found as much as 435 m further along the bulldozed trail inside the forest after one year

(Figure 2). The native grass Uniola virgata spread from the end of the bulldozed trail cross-

transect (555 meters) to beyond the fire region and into the area where M. maximus and L.

leucocephala established (Figure 2).

67

Figure 2: Post-bulldozing dispersal pattern of M. maximus, L. leucocephala and U. virgata

along the bulldozed trail during (A) summer 2012, (B) winter 2012 and (C) summer 2013.

Note: Locations where none of the three species occurred were dominated only by sprouting

trees other than L. leucocephala. Gaps presence between distances represent areas dominated

only by sprouting trees.

68

R² = 0.3599 R² = 0.0848

R² = 0.4211

0

1

0

1

15 65 115 165 215 265 315 365 415 465 515 565 Pre

sen

ce o

f sp

eci

es

in b

ulld

oze

tra

il d

uri

ng

sum

me

r 2

01

2

Distance from Road (meters)

M. maximus U. virgata L. leucocephala Log. (M. maximus) Log. (U. virgata ) Log. (L. leucocephala )

R² = 0.209 R² = 0.4635

R² = 0.2311

0

1

0

1

15 65 115 165 215 265 315 365 415 465 515 565 Pre

sen

ce o

f sp

eci

es

in b

ulld

oze

tra

il d

uri

ng

w

inte

r 2

01

2

Distance from Road (meters)

M. maximus U. virgata L. leucocephala Log. (M. maximus) Log. (U. virgata ) Log. (L. leucocephala )

A

B

69

R² = 0.2532

R² = 0.5016 R² = 0.3464

0

1

0

1

15 65 115 165 215 265 315 365 415 465 515 565

Pre

sen

ce o

f sp

eci

es

in b

ulld

oze

d t

rail

du

rin

g su

mm

er

20

13

Distance from Roads (meters) M. maximus U. virgata L. leucocephala Log. (M. maximus) Log. (U. virgata ) Log. (L. leucocephala )

C

70

We developed occurrence probability models, via logistic regression, for invasive

grasses (Table 1), native grasses (Table 2) and introduced tree species (Table 3) along the

555-m bulldozed trail. With respect to M. maximus colonization, increasing distance (i.e.,

three-dimensional distance with elevation gradient embedded; β0+β1 (Dist_z), β1< 0) from

the roadside starting point to the end of the bulldozed trail had a negative influence on

occurrence probability (β = -1.0803, SE = 0.2788; P = 0.0001) during the year-long study

cycle (Figure 2).

Figure 3: Logistic regression of invasive grasses occurrence model (β0+β1 (Dist_z),

β1< 0) of colonization from road side to bulldoze cross-transect end region at 600

meters range.

(β = -1.0803, SE = 0.2788;

P<0.0001)

71

M. maximus presence decreased as the distance from road increased (β= -1.0071, SE

= 0.2872; P = 0.0004). Dry seasons of summer 2012 and distance effect in combination were

shown to have a negative influence on invasive grasses occurrence probability (β=-1.7721,

SE=0.6904; P = 0.0103), no significant effect of rainy season on winter 2012, and significant

negative influence again on summer 2013 (β=-0.8535, SE=0.3985; P = 0.0322). To examine

seasonal rainfall effects on invasive grass colonization, a distance and rainy season model

was developed excluding summer dry seasons influence and attested no significant influence.

The bulldozed trail crossed the region burned after the fire (β0+ β1 (Fire), β1< 0), fire region

(β=-1.7444, SE=0.7818; P = 0.0257) and dry season (β= -1.5539, SE= 0.6427; P = 0.0156)

effect on invasive grasses colonization proved to negatively influence invasive grasses

progress. If competition between native and invasive grasses influenced Megathyrsus

maximus spread, it could not be assessed after one year, because model combining the

presence of Uniola virgata (NatG) + distance from road was not significant (β= -0.7259, SE=

0.5124; P = 0.1565).

72

Table 4. Statistics for models of M. maximus probability of occurrence derived from cross-

transect surveys conducted along the 555-m bulldozed trail in the Guánica Dry Forest reserve

section of Ensenada. All models are set under 95% confidence interval set. (*) Preferred

model.

Models Number of

Parameter

AICc ΔAICc AICc

Weight

Cum.

Weight

Likelihood

(LL)

Null 1 129.14 21.08 0.00 1.00 -63.55

Distance 2 112.10 4.04 0.11 0.90 -53.99

Distance +

Distance2

3 113.84 5.79 0.04 1.00 -53.81

Distance + Wet

Season

3 113.51 5.45 0.05 0.95 -53.65

*Distance +

Time

4 108.05 0.00 0.80 0.80 -49.84

Fire + Time 4 121.44 13.39 0.00 1.00 -56.54

Native Presence 2 129.04 20.99 0.00 1.00 -62.47

The U. virgata occurrence model was based on the species’ colonization progress

from the end-point of the bulldozed trail (i.e., in the burned forest area) and toward its

starting point at PR-325.. Increasing distance from road side proved to be strongly significant

in positive detection of native grasses (β= 2.4745, SE= 0.4604; P = 7.68e-08) considering the

historical establishment of native grasses inside the forest prior to disturbance (Figure 3).

73

Distance from road increased (β = 3.9951, SE= 1.2652; P = 0.0015) native grasses

colonization, as Uniola re-entered or regenerated in the bulldozer trail in areas where it had

previously been established. The first dry season, in combination with the distance effect, had

a strong negative effect (β = -8.0797, SE = 2.1893; P = 0.00022) on Uniola presence, but

including the effects of subsequent seasons did not improve model predictions. However,

when dry seasons were excluded from the model, winter 2012 showed to have significant

Figure 4: Logistic regression model of native grass occurrence, based only on

distance (β0+β1 (Dist_z), β1>0).

β = 2.4745, SE = 0.4604;

P =7.68e-08

74

positive influence (β = 1.3927, SE = 0.6545; P = 0.0334) on native grass colonization,

increasing as well the effect of distance from roads (β = 2.6591, SE = 0.5028; P = 1.23e-07).

Table 5. Statistics for models of U. virgata probability of occurrence based on cross-transect

surveys conducted along the 555-m bulldozed trail in the Guánica Dry Forest reserve section

of Ensenada. All models are set under 95% confidence interval set. (*) Preferred model.

Models Number of

Parameter

AICc ΔAICc AICc

Weight

Cum.

Weight

Likelihood

(LL)

Null 1 145.74 102.73 0.00 1.00 -71.85

Distance 2 83.20 40.19 0.00 1.00 -39.55

Distance +

Distance2

3 81.96 38.95 0.00 1.00 -37.87

Distance + Wet

Season

3 80.35 37.34 0.00 1.00 -37.07

*Distance +

Time

4 43.01 0.00 1.00 1.00 -17.32

Fire + Time 4 87.80 44.79 0.00 1.00 -39.72

Invasive

Presence

2 145.64 102.63 0.00 1.00 70.77

Increasing distance from the road decreased (β = -1.1257, SE = 0.2607; P = 1.58e-05)

on L. leucocephala occurrence over the year (Figure 4).

75

The quadratic effect on the distance from road was slightly positive and significant

(β= 0.5982, SE = 0.2760; P = 0.0302) which implies that L. leucocephala projected

movement in the bulldoze trail will continue effectively in the long-run. A model

representing L. leucocephala sharing the same location as invasive grasses had a positive

influence on probability of occurrence (β = 1.2730, SE = 0.4545; P = 0.0051), while such

interactions with native grasses was showed to be slightly negative (β = -0.9514, SE = .4812;

P = 0.0480). Dry seasons effect in combination with distance from road appeared not to favor

the spread of Leucaena in the short-run (β = -1.1443, SE = 0.4899; P = 0.0195), having the

Figure 5: Logistic regression model of L. leucocephala occurrence, based only on

distance (β0+β1 (Dist_z), β1<0).

(β = -1.1257, SE = 0.2607;

P = 1.58e-05)

76

same influence than the bulldoze trail distance to travel. However, after the rainy and mild

temperatures in winter 2012, were shown to have a significant positive effect (β = 1.1443, SE

= 0.4819; P = 0.0195) on L. leucocephala movement deep into the forest through the

bulldozed trail. When dry and wet seasons were combined within distance from road model,

only distance from road and summer 2012 had a significant negative influence (β = -1.6867,

SE = 0.6611; P = 0.0107) on L. leucocephala dispersal. Preliminary observation of fire

region and time effect model on L. leucocephala occurrence probability showed a negative

effect of post-fire conditions (β = -1.2993, SE = 0.6035; P = 0.0313).

Table 6. Statistics for models of L. leucocephala probability of occurrence based on cross-

transect surveys conducted along the 555- m bulldozed trail in the Guánica Dry Forest

reserve section of Ensenada. All models are set under 95% confidence interval set. (*)

Preferred model.

Models Number of

Parameter

AICc ΔAICc AICc

Weight

Cum.

Weight

Likelihood

(LL)

Null 1 144.23 30.61 0.00 1.00 -71.10

Distance 2 122.33 8.72 0.01 1.00 -59.11

Distance +

Distance2

3 119.73 6.12 0.04 0.99 -56.76

Distance + Wet

Season

3 118.77 5.15 0.07 0.95 -56.28

*Distance +

Time

4 113.61 0.00 0.88 0.88 -52.62

Fire + Time 4 134.73 21.12 0.00 1.00 -67.14

Invasive grass

Presence

2 142.01 28.39 0.00 1.00 -68.95

Native grass

Presence

2 144.23 30.61 0.00 1.00 -71.10

77

4.0 Discussion

Historically, native grasses have thrived in this tropical dry forest without

aggressively competing with native woody vegetation inside the undisturbed forest. Once a

major disturbance occurs, the landscape is vulnerable to invasion by highly competitive non-

native grasses and introduced tree species. More importantly, we observed some of the

mechanisms that promote plant invasions. For example, the bulldozed trail started directly on

a local road with heavy traffic (Freitas et al., 2010) and substantial roadside presence of M.

maximus. This generated high propagule pressure with respect to this grass, which is known

to be an aggressive invader of tropical dry forests due to its tolerance of drought and fire,

abundant wind-dispersed seeds, and ability to establish quickly in a variety of conditions,

especially in disturbed sites. Indeed, the likelihood of invasion by M. maximus increases

greatly in disturbed areas where little competition is offered by the remaining local

vegetation (Santiago et al., 2008).

We assume that M. maximus colonized the bulldozed trail from road PR-325 since it

was absent inside the forest for the first few months after the fire caused by the downed

power-line. . At any rate, the probability of finding M. maximus at a location along the

bulldozed trail declined from 70% near the trail’s starting point to less than 20% in the forest

interior, when it appears to have been confronted by biotic constraints such as woody sprout

regeneration and native grasses. According to the AICc Weight analysis for M. maximus, U.

virgata and L. leucocephala movement, the [Distance + Time] model was the best-

performing model for estimating the probability of species occurrence along the bulldozed

trail. However, even if this model worked according to expectations, the study time window

78

was too short to observe significant presence of invasive grasses inside the fire region, of

Melinis repens, although M. maximus managed to spread 360 m along the bulldozed trail,

and into the mature forest, by the end of the study. Over the same timeframe, U. virgata

managed to colonize and spread evenly from the end of the fire region to the mid-section of

the bulldozed trail, just 165 m from the road. Since this native species was already

established in patches throughout the forest and alongside the bulldozed trail, U. virgata had

the opportunity to colonize or sprou from multiple locations along the disturbed area and

build new colonies quickly. In just about a year of study, U. virgata regenerated quickly from

stolon residues that survived the fire or from seed dispersal into the post-bulldozed trail, and

colonized more efficiently than M. maximus in the fire region due to its historical presence in

the surrounding undisturbed forest. However, U. virgata declined in presence abruptly near

the mid-section of the bulldozed trail, which was instead dominated by woody sprouts.

Leucaena leucocephala colonized the first 45 m of the bulldozed trail from the roadside

during summer 2012, and then spread at at the same rapid pace, and colonized the same

areas, as M. maximus, . By the end of the study, L. leucocephala individuals were present

even at 435 m away from the trail’s start.

5.0 Conclusions

The spread of Leucaena leucocephala this deep into the forest region demonstrated

how surprisingly quick an introduced generalist tree species could colonize the open niche in

just one year. This is particularly important since native tree species struggle to re-colonize

open niches dominated by grasses, since they tend to grow slowly and require more energy

79

from the system (Ramjohn et al., 2012). Our study was consistent with previous research,

which demonstrated that Leucaena leucocephala (Parrotta, 2000) individuals can establish

themselves relatively quickly in disturbed sites shared by invasive grasses such as M.

maximus, based on an outstanding growth rate and low mortality rate (Wolfe and Van Bloem,

2012). Thus, if this pioneer generalist tree manages to establish itself before grasses, then

native tree seedlings will have a better chance of regenerating in the same niche (Santiago-

Garcia et al., 2008). The value of L. leucocephala in Puerto Rican dry forest stands goes

beyond competing with grasses to overcome hysteresis and fixating nitrogen in the soil

(Erickson et al., 2002). This species can provide an important pathway in re-establishing

native trees effectively in future management purposes (Ramjohn et al., 2012). Effective

forest management practices can greatly facilitate conservation initiatives when plant

invasions, native plant regeneration and fire regime interactions are inter-connected aspects

of the overall ecosystem dynamics (Brooks et al., 2004).

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