Population Dynamics of the Island Torrey Pine (Pinus Torreyana Ssp

Population Dynamics of the Island Torrey Pine (Pinus torreyana ssp. insularis) on Santa Rosa Island, CA

An Environmental Science and Resource Management Capstone Project

by Travis Hall and Andrew Brinkman

Submitted in partial fulfillment of the requirements for an Environmental Science and Resource Management Bachelors of Science degree from California State University Chanel Islands.

May 12, 2015

1 Table of Contents A bstract (Andrew B rinkm an & Travis H all)...... 4 Keywords (Andrew Brinkm an & Travis H a ll)...... 4 Introduction (Andrew Brinkm an & Travis H all)...... 4

Island History (Andrew Brinkman & Travis H all)...... 5 Island vs Mainland Natural History (Andrew Brinkman & Travis Hall)...... 5 Stand Spatial Structure (Andrew Brinkman & Travis Hall)...... 6 Seed dispersal and recruitment (Andrew Brinkman & Travis Hall) ...... 6 Study Objectives (Andrew Brinkman & Travis Hall)...... 7 Methods (Andrew B rinkm an & Travis H all)...... 7-12 Study Site (Andrew Brinkman & Travis Hall)...... 7 Census (Travis Hall)...... 7-8 Age Structure (Travis Hall)...... 8 Demography Plots (Travis H all)...... 8-9 Interpopulation Comparison (Travis H all)...... 9 Quantifying Reproductive Habitats (Andrew Brinkman)...... 9-10 Leaf litter and Precipitation effects on Seedlings Germination and Survival (Andrew Brinkman)...... 10-12 Results (Andrew B rinkm an & Travis H all)...... 12-23 Census (Travis Hall)...... 12-13 Age Structure (Travis Hall)...... 13-14 Demography Plots (Travis H all)...... 14 Interpopulation Comparision (Travis Hall)...... 15-16 Quantifying Reproductive Habitats (Andrew Brinkman)...... 17-18 Soil texture and Volumetric Water Content of island Torrey pine grove soils (Andrew Brinkman)...... 19-20

Leaf litter and Precipitation effects on Seedlings Germination and Survival (Andrew Brinkman)...... 21-23

Discussion (Andrew Brinkm an & Travis H all)...... 24-27 Census (Travis Hall)...... 24 Age Structure (Travis Hall)...... 24 Demography Plots (Travis H all)...... 24-25 Interpopulation Comparision (Travis Hall)...... 25

2 Quantifying Reproductive Habitats (Andrew Brinkman)...... 25-26 Soil texture and Volumetric Water Content of island Torrey pine grove soils (Andrew Brinkman)...... 26

Leaf litter and Precipitation effects on Seedlings Germination and Survival (Andrew Brinkman)...... 26-27

Conclusion (Andrew Brinkman & Travis Hall)...... 27-28

Acknowledgments (Andrew Brinkman & Travis Hall)...... 28

References (Andrew Brinkman & Travis Hall)...... 29-31

3 Abstract

Torrey pine (Pinus torreyana and Pinus torreyana ssp. insularis) is the rarest pine species in North America, with populations limited to Del Mar, CA and Santa Rosa Island (SRI), CA (IUCN 2013). Over the past 150 years, grazing by non-native ungulates and ground disturbance by feral pigs resulted in landscape level disturbance, erosion, and negative impacts to island flora (Moody 2000). We completed a census on the SRI Torrey pine population to determine (a) its population size and whether it is stable, growing, or declining; (b) the spatial variation in population structure; (c) the spatial patterning of trees in different life stages; (d) the environmental factors that are related to germination and seedling recruitment; and (e) the conservation gains associated with non-native ungulate removal. In total, 24,194 individuals make up the SRI Torrey pine population, 3,062 of which are sexually mature. The proportion of juveniles to adults for SRI is 7:1, compared to Del Mar’s 1:2. SRI’s population is dominated by younger trees: 79% are < 160 cm tall. Cores were taken from 19 trees of different sizes to determine the relationship between diameter at breast height and age. We tested distance bands (m) of trees that had the most seedlings & saplings with high and low densities using a local Moran’s I test within ArcMap. Results were then used in a hot spot analysis to find significant recruitment areas within 3 groves (p<0.01). We evaluated the recent recruitment by sampling reproductive trees (n=31) for seeds. Soil and leaf litter were also collected from reproductive areas (n=24) across the population. On December 31, 2014 we conducted a common garden experiment to evaluate the effect of leaf litter and precipitation on germination (time and success) and seedling survival. We are continuing to monitor the survival and growth rate of the plants in 45, 10 x 10 m permanent plots. Results from this study will provide resource managers with the current areas of reproduction and environmental variables associated with the reproductive success of the SRI Torrey pine.

Keywords

Census, Reproduction, Demography, Restoration, Endemic, Torrey Pines, Santa Rosa Island, Channel Islands National Park

Introduction

Torrey pine (Pinus torreyana) is the second rarest species of pine in the world and the rarest in North America (IUCN 2013). Currently, natural populations only occur on Santa Rosa Island (SRI), CA and in Del Mar, CA within Torrey Pines State Natural Reserve (TPSNR). The SRI Torrey pine population (Pinus torreyana Parry ex Carriere ssp.insularis J.R. Haller) (Haller 1986) has been exposed to a myriad of human impacts and introduced species (Thompson and West 1883). Even though TPSNR has had some form of protection since 1885, urban sprawl and outbreaks of bark beetle have greatly affected this isolated population (Reserve 2013). This study provides demographic data to understand the population and geographic distribution of P. torreyana ssp. insularis and compares the population structures of both locations in light of their disturbance histories. The Channel Islands are places of endemism as well as recipients of introduced species (Moody 2000). We focus on the population characteristics of an island endemic by studying the island Torrey pine, and by doing this will inform the scientific community how the island is recovering from the removal of introduced non-native ungulates.

4 Island History

Historical accounts described the northern Channel Islands full of grasses, shrubs, trees, and cactus (Aaron 2000). On SRI grazing from non-native animals such as sheep (Ovis aries), cattle (Bos taurus), Roosevelt elk (Cervus elephas), and mule deer (Odocoileus hemionus) and ground disturbance by feral pigs (Sus scrofa) occurred between 1844 and 2013 when the last of the non-native ungulates were removed from Santa Rosa Island by the National Park Service (McEachern et al. in press). By the mid-1800s the island contained between 60,000 and 100,000 sheep and about 8,000 cattle; deer and elk were introduced around 1880 and managed at around 600 to 1000 animals annually for commercial hunting (Livingston 2006). Pigs were likely introduced to the island around 1853 (Lombardo and Faulkner 1999). Grazing and ground disturbance by feral pigs on the Channel Islands resulted in widespread conversion of woody vegetation to non-native annual grassland (Moody 2000). In 1888, botanist T. Brandegee collected a Torrey pine specimen from SRI, noting a scattered stand of about 100 trees (Junak et al. 2007). During the 1960’s SRI was reported to contain around 1000 mature Torrey pines (Zavarin et al. 1966). In the 1980s the population was estimated around 2000 (Ledig and Conkle 1983). The current population remains unknown and is a primary focus of this study.

Island vs. Mainland Natural History

Pinus torreyana of both varieties are in the family of large cone pine species that include P. coulteri and P. sabiniana. But unlike the other pine species in this group, Torrey pine is the only species that exhibits an ecological affinity for maritime habitats, which is more typical of small cone pine species, such as Monterey pine (Pinus radiata) (Wells and Getis 1999).

The common ancestor of Torrey pine may have been more widespread (Raven and Axelrod 1978), however, the current limited distribution has been hypothesized as an adaptation to the pressures of climate change through the late Pleistocene and Holocene (Anderson et al. 2010). The current limited genetic variability within the TPSNR population is most likely explained by genetic drift when the population was reduced to less than 50 individuals as a result of intensive warming during Xerothermic period 8500 to 3000 B.P. (Ledig and Conkle 1983). Genetic variability is also extremely limited within the SRI population and is likely explained by a founder effect by bird caching during the era of Santarosea when the island was 6-7 km offshore of San Diego (Ledig and Conkle 1983). The two populations exhibit unique morphology (needle color, height, cone shape, seed size) proven to be retained in a common garden planting (Haller 1986).

During the last glacial maximum, the northern Channel Islands were one continuous island called Santarosae. According to the Santa Barbara basin pollen record, conifers like Douglas fir (Pseudotsuga menziesii ssp menziesii), cypress (Cupressus goveniana), and Bishop pine ( Pinus muricata) were present on the larger Santarosae, suggesting a forested environment more typical of the central California coast seen today (Williams et al. 2008, Rick et al. 2012). A pollen record from SRI shows that as the Pleistocene passed and Holocene entered, the climate warmed and the conifer forest was succeeded by scrub and grasslands (Anderson et al. 2010). Stands of other coastal conifers suffered the effects of climate change, resulting in wide spread die-offs (Heusser 1995).

5 Stand Spatial Structure

Stand structure is determined by the tree’s life history, quality of habitat, climatic variation, and disturbance (Wells and Getis 1999). Wells and Getis (1999) found that younger stands at TPSNR tend to be more aggregated than older stands, in addition to younger trees being more aggregated at closer distances while older trees cluster at greater distances. Critical distance is the distance at which clustering is maximized, that is, the distance at which the rate of clustering is greatest when compared to complete spatial randomness (CSR). The critical distance for Torrey pines on SRI is 19 meters, while the critical distance at TPSNR is 9 meters inside East Grove (Wells and Getis 1999). It is uncertain how stand structure will respond to the removal of non native ungulates.

Seed dispersal and recruitment

Torrey pines on SRI are located on loamy sands with rocky outcrops (USDA 2007). Torrey pine seed cones typically open 6 months after maturity and lose the majority of their seeds within 2 years (Johnson et al. 2003). Extreme weather conditions may be required for long distance dispersal (LDD) but are rare in nature (Nathan et al. 2008). Many plants rely on members of the Corvidae family as a source of seed dispersal (Nogales 1999). Young trees are growing in coastal plains 400 m from the nearest reproductive individual, suggesting LDD could be taking place on SRI (pers. obs.). With common ravens (Corvus corax) likely preferring other sources of nutrition such as carrion over Torrey pine seeds, most seed dispersal for Torrey pine is short distance dispersal (SDD) by deer mice (Peromyscus maniculatus) with mean transport distance of 7.35 m (Vander Wall and Joyner 1998, Johnson et al. 2003). Common ravens are responsible for some LDD but the majority of seeds fall within 3.4 m of parent trees, landing within Torrey pine understory (Johnson et al. 2003, Siepielski and Benkman 2007).

Island Torrey pine understory consists of substantial and deep leaf litter. In a study conducted on within TPSNR, McMaster (1980) concluded that Torrey pine seedlings are shade intolerant. Areas of open canopy provide habitat for island Torrey pine recruitment and competition amongst island flora such as California live oak (Quercus agrifolia), Santa Rosa Island manzanita (Arctostaphylos confertiflora), scrub oak (Quercus pacifica), and chamise (Adenostoma fasciculatum) (Junak 2007). Many of these larger woody plants that now appear in the understory may have recruited when the stand was smaller with little canopy cover. These plants typically don’t recruit in shaded understory conditions, thus their presence suggests that past habitats were more open, a time when the stand was smaller and competing species were recruiting outside the grove in open habitat.

From observation, the island Torrey pine grove edge provides the most suitable habitat for seedling germination and survival; however, little is known of the effect of leaf litter and precipitation on recruitment and seedling survival of P. torreyana ssp. insularis. Many Pinus species depend on leaf litter for seedling germination and survival (Williams et al. 1990). However, significant leaf litter depth has been known to inhibit seedling germination due to changes in light availability and soil chemistry (Hillhorst and Karssen 2000, Jensen and Meyer 2001). Investigating the relationship between rainfall and leaf litter provides an understanding of the current reproductive habitat and future of the island Torrey pine.

6 Study Objectives

The island Torrey pines on SRI have been studied by many researchers (Zavarin 1966, McMaster 1980, Ledig and Conkle 1983, Haller 1986, Wells and Getis 1999, Johnson et al. 2003, Williams et al. 2008), but basic information like population aggregation, demographics, and reproduction have not been recently investigated. This study provides baseline data to answer questions on: 1) What is the population size and structure? (2) How are the trees distributed across the island? (3) What are the recruitment and survival rates across the stand? (4) What is the relationship between tree diameter and age? (5) How does the island population compare to the mainland population? (6) Where are areas of significant recruitment? (7) What are the effects of leaf litter and precipitation on germination rate, probability and seedling survival?

Methods

Study Site

Santa Rosa Island (214 km2) is located 42 km offshore of Santa Barbara, CA within the Channel Islands National Park. The population is on a north-facing marine terraces and are approximately 5 km southeast of the pier and CSU Channel Islands’ Santa Rosa Island Research Station. Climate on SRI is Mediterranean, precipitation typically occurs between October and April. Prevailing northwest winds blow over the island year round, with gusts reaching 40 knots per hour(Center 2013). Yearly precipitation in the form of rain has been positively correlated with growth and survival of individuals in addition to the influence of overcast cloud cover and summertime fog (Biondi et al. 1997, Wells and Getis 1999, Williams et al. 2008).

Census

Franklin and Santos (2010) performed a census at TPSNR in 2006, recording location, diameter at breast height (DBH), stage classification (adult (trees taller than 160 cm with cones); sub-adult (>160 cm without cones); saplings (30-160 cm tall); and seedlings (<30 cm tall)), and presence of cones for every Torrey pine in the reserve. In order to compare populations, we performed a complete census of the SRI Torrey pines from January to July 2014 using a similar methodology. To understand the population’s health, we added an attribute of tree health by estimating percentage of living needles and branches. The SRI Torrey pines were observed by Wells and Getis (1999) to be browsed and rubbed by elk and mule deer, resulting in greater lateral growth and multiple stems. Some individuals older than 25 years were less than 1.45 meters tall. Thus, we also recorded the number of stems on individual trees as an indication of ungulate herbivory. Trees were considered reproductive if the plant had reproductive structures present.

We collected the following data for every tree with a DBH > 4 cm: 1) GPS location (< 3 m), 2) DBH of the largest stem, 3) number of stems at breast height, 4) presence of cones, 5) health classification (>50% living, <50% living, dead), 6) height classification (Table 1) and seedlings

7 and saplings under the canopies of reproductive trees. To account for the high number of small individuals under the canopies of reproductive trees, we recorded the number of seedlings and saplings as an attribute of the nearest tree with a DBH > 4 cm. Torrey pines that had a DBH < 4 cm and were not under a mature Torrey pine’s canopy were recorded individually for the same parameters aforementioned.

Table 1 Height classification for island Torrey pine population.

Class 1 <30 cm

Class 2 30-160 cm

Class 3 161-300

Class 4 301-600 cm

Class 5 600+ cm

Age Structure

To determine the relationship between DBH and age, we cored 19 SRI Torrey pines spanning the range of sizes present. To obtain accurate and consistent rings we only cored trees with a single vertical stem that had an accessible trunk, free of low hanging branches that would prevent us from reaching the base. We selected trees that represented a variety of DBH size classes that we encountered as we hiked through Main Grove. We extracted two cores from opposite sides of the trees along the contour of the slope so as to avoid exaggerated ring growth on the downhill side (Jonsson et al. 2002). We extracted cores as close to the base as the increment borer would allow, so as to capture the most growth rings in the tree. After the cores dried for a week, we sanded them until all rings were apparent and counted the darker bands of growth (late wood) on both samples. We used the mean of the two late wood counts to assign age. We plotted the DBH of each tree against its estimated age and performed a linear regression analysis to see the relationship between DBH and age.

Demography Plots

There are four spatially distinct groves, which were labeled: North Grove, Cogan Grove, Main Grove, and Box Canyon (Figure 2). In order to find the densities of the reproductive trees in each grove, we employed the point density tool in ESRI ArcMap 10.2 to find the density of reproductive trees > height class 4. The cell size was set to 10 m so that every cell represented a 100 m2 plot with uniform density (Franklin and Santos 2010). For practicality, we restricted the output of the spatial analysis to four density classes using natural breaks in the distribution.

To study the life history of individual trees and the environmental conditions within the different grove densities, we established square 100 m2 permanent monitoring plots. We randomly selected data points within each of the 4 density classes to stratify the distribution of plots. Plots were not allowed to be touching other plots and had to have uniform aspect so that plot comparisons would be consistent. Every adult Torrey pine within the plot was given an aluminum tag approximately 2 m above the ground on the south side of the tree and was measured for the

8 same attributes as in the census. Seedlings and saplings were given aluminum tags and were measured from the base to the tallest part of the plant. We recorded presence or absence of pine needle cover, identified all plant species by genus and made an estimate of foliar cover within the 10 x 10 m plot, classified soil texture (rocky or sandy) by hand in the field, and measured slope aspect using a compass within each plot. In total we created 45 permanent plots spread over the four groves.

Interpopulation Comparison

We compared mainland and island size classes by using Franklin and Santos’s (2010) size classification system. A 2 x 2 Chi-square test was used to test if the demographic proportions in each population were similar. The distribution of tree diameters > 4 cm DBH for both populations were analyzed using an f-test and a t-test to determine if there was a significant difference in the variance and mean size, which can also suggest a difference in age structure.

At TPSNR, Franklin and Santos (2010) found the trees to be distributed in a cluster pattern by using Ripley's K function, a multi-distance spatial cluster analysis. This test compares the locations of all observed data points against CSR. In ArcMap we used Ripley’s K function to find the critical distance of all SRI Torrey pines with cones for both the SRI and TPSNR population, with Ripley’s K edge correction formula (Franklin and Santos 2010). We selected reproductive trees to look at the adult distribution. We used the average nearest neighbor test to better understand the spatial distribution of reproductive trees on SRI and TPSNR (Gao 2013).

Quantifying Reproductive Habitats

The island Torrey pine habitat varies dramatically across the population. There are many environmental variables that may affect individual morphology, seed distribution and recruitment. During our initial census we observed high densities of seedlings (0-30cm) and saplings (30 160cm) along the edge of the reproductive (cones present) population. Edge habitats are identified with high numbers of seedlings and saplings, greater wind exposure, less leaf litter depth and open canopy cover. Core habitats are identified by a lack of seedlings and saplings, less wind exposure, deeper leaf litter and closed canopy cover.

In order to quantify these habitats we selected reproductive trees with recruitment (seedlings + saplings) within parent tree canopies. We performed a Global Moran’s I and Hot Spot Analysis (zone of indifference) using ArcMap on three independent groves using set distance bands conducted a total of 10 times per grove (Main Grove=30 m, Cogan Grove=2 m and North Grove=5 m). Final distances chosen correspond with the greatest z-score and significant p-values for each grove.

We further characterized the edge and core habitats by measuring leaf litter depth (cm) and soil moisture near reproductive trees sampled for seeds. Soil samples (n=24) were collected from a 10 cm depth to identify top soil type across each grove. We recorded average volumetric water content (n=3) for each soil sample using a Fieldscout TDR 300 Soil Moisture Meter with a 18 cm long soil probe for sandy soil types. All soil samples were weighed at 5 g and placed into test tubes with deionized water and shaken vigorously. Sediment was suspended and allowed to settle for 24 hours before measuring proportions of clay, silt and sand. We recorded samples as (1) loamy sand, (2) sand, or (3) sandy loam (Juma 1999). We tested the effect of leaf litter depth (cm) on soil

9 moisture between edge and core samples using a linear regression. Additionally, we collected island Torrey pine leaf litter for the common garden experiment.

Figure 1: Sampling o f seeds and soil from the Santa Rosa Island Torrey pine reproductive population across 3 groves. Reproductive trees shown are classified with the presence o f cones.

Leaf litter and Precipitation effects on Seedling Germination and Survival

We collected cones from a total of 31 reproductive trees occurring across 3 groves (Main Grove, Cogan Grove, North Grove). Reproductive trees were selected upon access to cones. All cones were dissected in the field and seeds were collected for the germination experiment.

On December 31, 2014 we simulated the island Torrey pine reproductive edge and tested the effects of leaf litter and annual rainfall on seed germination rate, proportion and seedling survival. A total of 200 seeds were selected at random (Becerra et al. 2004) from a homogenized seed bank collected across 3 groves (Main Grove, Cogan Grove and North Grove). All seeds were stratified by refrigeration for 43 days at 3° C and soaked for 24 hours prior to planting to break dormancy (McMaster and Zedler 1980).We planted seeds in four 27cm x 54 cm trays (0.15 m2) with a soil mixture of loamy sand that best represented island Torrey pine habitat (IST Association 1999, United States Department of Agriculture 2007). Island Torrey pine seeds were assigned four treatments: (1) high precipitation with island Torrey pine leaf litter, (2) high precipitation without leaf litter, (3) low precipitation with leaf litter and (4) low precipitation without leaf litter. We covered two trays with 2.5 cm of island Torrey pine leaf litter collected in Fall 2014, based off of average depth measured in edge reproductive habitats (Figure 9).

Watering treatments were simulated from high precipitation (HP) and low precipitation (LP) years observed from 1999 to 2014 at a weather station on SRI (WRCC 2014) (Table 2). We

10 selected 1999 as the start date due to the first year of removing of cattle from the island (McEachern et al. 2009). Total precipitation occurring across 16 years for the months of January, February and March were divided in half by HP and LP, where the mean was calculated for each of the two precipitation treatments. The irrigated quantity for each precipitation treatment was based off of the mean value for HP (200 mm) and LP (78 mm) years (Becerra et al. 2004) (Table 2).

On December 31, 2014 we planted seeds in a greenhouse at CSU Channel Islands protected from ambient precipitation and wind. Temperature and humidity was recorded over the 3 month period (Tables 3, 4). We simulated 4 unique microhabitats by choosing 50 seeds to be planted in 1 of 4 trays. Seeds were evaluated independently within each treatment for statistical purposes (Oksanen 2001). We irrigated seeds under January, February and March precipitation conditions three times per week for 3 months (Table 2). We recorded germination time as the time elapsed in days from the beginning of watering before a 3mm radicle emergence (McMaster and Zedler 1980).

Table 2: Monthly distribution o f irrigation (mm) supplied to high precipitation(HP) and low precipitation(LP) per treatment.

Month HP LP

January 54 29

February 97 25

March 49 24

Total 200 78

Table 3: Monthly temperatures (°F) for January, February and March. High, low and mean temperatures reported at CSU Channel Islands green house.

Month High Temperature (°F) Low Temperature (°F) Mean Temperature (°F)

January 85 38 61

February 99 43 62

March 91 45 65

Table 4: Monthly humidity for January, February and March. High, low and mean humidity reported.

Month High Humidity% Low Humidity % Mean Humidity %

January 97 24 66

February 97 19 73

March 96 27 69

11 We used a two-way ANOVA (SPSSv.22) to evaluate the effect of HP and LP without leaf litter and high precipitation with leaf litter on germination time of viable seeds (n=83). Probability for seed germination was recorded daily. We removed the low precipitation without leaf litter treatment due to its low sample size (n=1) from the ANOVA analysis.

We used a logistic regression (SPSSv.22) to evaluate the effect of leaf litter, precipitation and leaf litter with precipitation on probability of germination and seedling survival (n=83). After 3 months we recorded seedlings for survival. We removed the no leaf litter and LP treatment due to its low sample size (n=1) from the logistic regression analysis. Results

Census

The SRI Torrey Pine population was composed of 24,194 individuals (Figure 2). The distribution of the SRI Torrey pine height classification can be seen in Table 5. The average number of seedlings per tree > 4 cm DBH was 1.0 (SE=2.0) while saplings had 1.5 (SE=1.5), with some trees having over 600 recruits nearby. There were 1,847 multi-stemmed pines, the majority of which had 2 or 3 stems, and 3,063 individuals had reproductive structures present. Of the entire SRI Torrey pine population, 74 were dead, 165 were < 50% alive, and the remaining were considered >50% alive.

Table 5 Height classification of 2014 census on SRI Torrey pines. Class 1 <30 cm 6,819

Class 2 30-160 cm 12,336

Class 3 161-300 1,435

Class 4 301-600 cm 1,140

Class 5 600+ cm 2,464

12 Figure 2: Torrey pines on Santa Rosa Island with trees > 60 cm DBH in red and all other trees in yellow.

Age Structure

We cored 19 trees and they had 9 to 49 growth rings. DBH had a significant relationship to growth rings, which are typically produced once a year (p<0.001, R2=0.65, y=1.08x+5.29). Using this model estimates that the largest tree (116 cm) is also the oldest (130 +/- 45 years). The average age of all Torrey pines > 4 cm DBH on SRI is 32 years +/- 11 (Figure 3).

13 Figure 3 Linear regression of DBH v. age (p<0.001).

Demography Plots

Plots were established in July 2014 and revisited in March 2015. The 45 demography plots were composed of 329 trees. The summary of their size classes from our initial survey and follow up are in Table 4. Average growth for seedling and sapling height was 3.2 cm (n=180) and DBH was 0.38 cm (n=124). In total, 25 tagged individuals died with all but one being height class 1.

Vegetation cover for the plots varied from 100% needle cover to exposed rock with other flora surrounding. Other flora found within the plots included: Arctostaphylos confertiflora crustacea ssp insularis, Chamise adenostoma fasciculatum ssp prostratum, Eriogonum grande var. rubescens, Salvia brandegeei, Quercus pacifica, Mimulus spp, Toyon heteromeles arbutfolia, Baccharis pilularis, Artemesia californica, Dudleya spp, and Avena spp.

Soil texture was sandy in 60% of plots while the remaining 40% was rocky. Majority of plots (71%) in the higher densities had a northern facing aspect, while plots in the lowest densities had aspects in all directions including sites that were relatively flat.

Table 4 Height class distribution of P. torreyana insularis within demography plots

Height Class Height (cm) July 2014 March 2015 Class 1 0-30 84 112 Class 2 30-160 122 122 Class 3 160-300 29 29 Class 4 300-600 23 20 Class 5 +600 71 73 Total 329 356

14 Interpopulation Comparison

The 2 x 2 Chi-square tests of adults to seedlings, adults to saplings, and adults to juveniles were significantly different in every combination between SRI and TPSNR (p<0.001, df=1) (Table 6). A non-parametric t-test revealed that the mainland DBH (30.9 cm) was significantly different (p<0.005) than the island (24.2 cm) (Figure 2). The critical distance for reproductive trees on SRI was 25 m, whereas on TPSNR it was 36 m. Clustering was above the upper confidence envelope at all distances up to 100 m for both populations. The SRI population showed significant clustering (p<0.005) with the average nearest neighbor at 8.2 m for adult trees. This is similar to the TPSNR population which showed a significant clustering (p<0.005) and an average nearest neighbor at 6.9 m for adult trees (Franklin and Santos 2010).

Table 5 Height composition of both populations

Sizes TPSNR SRI <30cm 262 6819 30-160 cm 448 12337 >160cm 878 2036 >160cm with cones 3806 3002 Total 5394 24194

15 Population Structure on SRI Population Structure on TPSNR Quantifying Reproductive Habitats

We classified reproductive habitats across three groves (Main Grove, Cogan Grove and North Grove) as those with a significant (p<0.01) number of seedlings and saplings within parent canopies, as shown in Figures 5 - 7. The Hot Spot analysis concluded a significant (p<0.01) presence of seedlings and sapling along the edges of the reproductive populations of Main Grove (60m, z=6.81, p=0.00), Cogan Grove (18m, z=6.94, p=0.00) and North Grove (25m, z=7.61 p=0.00). A significant (p<0.01) absence of seedlings and saplings are shown in cold spots from Main Grove and North Grove. Cogan Gove lacked any significant (p<0.10, 0.05, 0.01) absence of seedlings or saplings.

Figure 5: Hot Spot Analysis (zone o f indifference 60 m) o f "Main Grove Reproductive Habitat" is shown using reproductive trees with seedlings & saplings associated within 10 m. Notable significant (p<0.01) number o f seedlings and saplings are found present on the edge o f the reproductive habitat and absent from core reproductive habitat.

17 Figure 6: Hot Spot Analysis (zone o f indifference 18m) result o f "Cogan Grove Reproductive Habitat". Reproductive trees are shown with seedlings & saplings associated within 10m. Notable significant (p<0.01) number o f seedlings & saplings are found present on the edge o f the reproductive habitat. There is no significant number o f seedlings & saplings present.

Figure 7: Hot Spot Analysis (zone o f indifference 25m) o f "North Grove Reproductive Habitat". Reproductive trees are shown with seedlings & saplings associated within 10m. Notable significant (p<0.01) number o f seedlings & saplings are found present on the edge o f the reproductive habitat and absent from core reproductive habitat.

18 Soil texture and volumetric water content of island Torrey pine grove soils

Soil texture analysis (n=24) across three groves (Main Grove, Cogan Grove and North Grove) resulted in the classification of loamy sand (n=11) as the dominant soil type for the SRI Torrey pine habitat. Sand (n=8) and sandy loam (n=5) are also notably present across the population.

Figure 8: Results o f soil texture analysis sampled from 10 cm depth (n=24). Count o f Loamy Sand, Sand and Sandy Loam determined by percent clay, silt and sand.

Linear regression of volumetric water content vs leaf litter depth resulted in an insignificant weak positive correlation (R2=0.16, p=0.15, n=12) across Main Grove, Cogan Grove and North Grove edge reproductive habitats. Core reproductive habitat resulted in an insignificant weak negative correlation (R2=0.0848, p=0.36, n=12) across Main Grove, Cogan Grove and North Grove.

19 Edge Average Volumetric Water Content vs Leaf Litter Depth

Figure 9: Positive correlation between soil moisture and leaf litter depth (R2=0.16, p=0.15, n=12).

Core Average Volumetric Water Content vs Leaf Litter Depth

Figure 10: Negative correlation between soil moisture and leaf litter depth (R2=0.08, p=0.36, n=12).

20 Leaf litter and Precipitation on Seedling Germination and Survival

From 200 seeds planted, 42% germinated and 67% of those seedlings survived after 3 months. The mean germination rate for treatments with high precipitation and without leaf litter were not significant (Figure 11). High precipitation and leaf litter (ANOVA df=1, p=0.607) and high precipitation without leaf litter (ANOVA df=1, p=0.206) were also not significant. Low precipitation with leaf litter increased germination rate (x=49.1days) however there was no significant interaction between the two variables.

Figure 11: Mean germination rate in days since planting. Low precipitation with leaf litter (49.1 days), high precipitation without leaf litter (54.2 days) and high precipitation with leaf litter (52.2 days).

All treatments proved to be statistically significant for increasing percent germination when compared to low precipitation without leaf litter. The presence of leaf litter proved to be most statistically significant (Logistic Regression p<0.01) followed by high precipitation (Logistic Regression p<0.01) and the interaction of high precipitation with leaf litter (Logistic Regression p<0.01). High precipitation without leaf litter increased probability of germination from 2% to 38% (Figure 12). Germination probability was also increased by the presence of leaf litter alone however, high precipitation with leaf litter (64%) and low precipitation with leaf litter (62%) appeared to have a similar effect on percent germination (Figure 12).

21 Figure 12: Germination probability after 3 months. Low precipitation without leaf litter (2%), high precipitation without leaf litter (38%), low precipitation with leaf litter (62%) and high precipitation with leaf litter (64%).

There was no significant difference for seedling survival for high precipitation without leaf litter (Logistic Regression p=0.48) or high precipitation with leaf litter (Logistic Regression p=0.67). Greatest survival occurred in low precipitation with leaf litter (77.4%) followed by high precipitation without leaf litter (68.4%). The lowest survival occurred in high precipitation with leaf litter (62.5%) (Figure 13).

Figure 13: Probability of seedling survival after 3 months. Low precipitation with leaf litter (77.4%), high precipitation without leaf litter (68.4%) and high precipitation with leaf litter (62.5%).

22 Germination Rate for the Island Torrey Pine

Figure 14: Island Torrey Pine germination rate in days since planting fo r high and low precipitation with the presence or absence o f leaf litter. Mean value germination days proved to be not significant across treatments. Low precipitation & no leaf litter was removed from Two-Way ANOVA due to an insufficient sample size (n=1).

Island Torrey Pine %Germination and Survival

Figure 15: Island Torrey Pine % Germination and Survival (n=83). Effect o f leaf litter (p<0.01), high precipitation (p<0.01) and high precipitation with leaf litter (p<0.01) on % germination was significant. Treatments had no significance on % survival.

23 Discussion

Census

Seedlings and saplings are found in great quantities on SRI. This increase in recruitment is likely contributed to the removal of ungulates, specifically mule deer and elk. Deer and elk browse young trees and seedlings, and can alter ecosystem dynamics for centuries (Cote et al. 2004, Tanentzap et al. 2011). Mule deer and elk have been observed to browse conifers, and being limited to SRI vegetation, this resulted in herbivory on island Torrey pine seedlings (Coomes et al. 2003, Nichols and Spong 2014). With 3,063 reproductive individuals, each has reproduced over 4 offspring on average that have survived beyond the seedling stage within the past 5 years.

Some plants have clearly been browsed and have more than 10 stems near the base (pers. obs.). Multi-stemmed trees can be indicators of browsing, but there are many plants that have germinated since ungulate removal that are developing two or three stems.

The overall health of the SRI population is very healthy with only 1% classified as dead, and 2% as < 50% living. This figure is probably underestimating all the dead seedlings that were well concealed amidst the leaf litter.

Age Structure

Almost 80% of the 24,194 Torrey pines on SRI are < 5 cm DBH, which are estimated to be less than 5 years old (Figure 3). The mean DBH of the SRI Torrey pine population is much lower than the reported average because most of the young trees were not included. They were not included because they were < 4 cm DBH during 2014. Such a plethora of recruits is indicative of a population that is expanding (Figure 4).

When comparing the calculated growth rate to the removal of feral pigs in 1993, cattle in 1998, mule deer in 2011, and elk in 2013, it is apparent that the removal of the last two has allowed more trees to survive in younger age classes (Figure 2) (unpublished data from CINP, Santa Barbara Museum of Natural History, Channel Islands unpublished archives). The removal of mule deer and elk shows the largest increase in the following size classes. While the last elk was removed late 2013, our data shows that the population began its massive increase in recruitment before the elk were completely removed. This is most likely the result of differences in foraging preferences between elk and mule deer (Roberts et al. 2014).

Demography Plots

The seedling stage showed the highest rate of mortality (29%) while saplings had a much lower mortality rate (<1%). Similar seedling survival rates (62%) and growths (2-3 cm) were reported in TPSRN in 2006-2007 (Franklin and Santos 2010). Seedlings had a net increase from 84 in July 2014 to 112 in March 2015 throughout all plots. Seedlings had a 71% survival rate, persisting through the fourth year of drought (WRCC 2014). With 3,063 reproductive individuals, each has reproduced over 4 offspring on average that have survived beyond the seedling stage within the past 5 years.

Over exposure can kill seedlings by drying them out. On the other hand, too much shading can deprive the growing plants of light (McMaster 1980). This ideal Torrey pine growing habitat

24 has both light and shade, access to water without being inundated, well drained sandy soils, leaf litter, and enough distance from neighboring trees to access to nutrients. These plots have revealed that during our first year of monitoring, shade has caused 88% of all mortalities. These seedlings were all heavily shaded by adult canopies and were growing through leaf litter up to 12 cm in depth.

Other vegetation in the high density plots is rare. Over shading, restricted water resources, and acidic needle cover may contribute to inhibiting floral diversity within the Torrey pine stands on SRI (Junak 2007).

Interpopulation Comparison

The ratio of juveniles to adults is 7:1 on SRI while there is only 1:2 ratio on TPSNR. The difference in proportions of adults and juveniles could be attributed partially to the open habitat created by grazing (Leopold 1924). TPSNR has not been as fortunate to have such large scale habitat opening. In 1972 a fire that killed 93 adult Torrey pines in TPSNR gave rise to only 220 saplings by 1979 (McMaster 1980). Comparing the same DBH class sizes between populations is not appropriate because many of the trees on SRI have experienced browsing pressure, thus resulting in trees that are small for their age (Wells and Getis 1999). Many of the smaller class sizes on SRI could be the same age as the bigger size classes at TPSNR. Given that information, there is still a disproportionally larger amount of recruits on SRI compared to TPSNR.

Quantifying Reproductive Habitats

We discovered edge habitats as areas with a significant presence of seedlings and saplings and core habitats as areas with a significant absence of seedling and saplings. Several environmental factors contribute to this difference between both habitats including: canopy cover, leaf litter depth, soil moisture, prevailing winds, soil microbial communities and seed dispersal (McMaster 1980, Hillhorst and Karssen 2000, Jensen and Meyer 2001, Johnson et al. 2003, Siepielski and Benkman 2007). Of all factors attributed to current reproductive habitats, limited dispersal appears to have the greatest impact on the current distribution of reproductive habitat. An over looked driver of seed dispersal may be contributed to cone morphology and seed retention. Female cones are more spherical allowing a capacity to roll downhill great distances (Haller 1986) and seeds after initial opening are known to be viable up to 10 years (McMaster and Zedler 1980, Haller 1986). We observed hundreds of cones piled up near the lowest point on respective NE hill sides near or within reproductive edge habitats. Once cones are shed from parent trees they tumble down the hill side towards the lowest point tossing seeds (pers. obs.). This “dispersal by gravity” may also be a contributing factor to the high density of recruitment found within reproductive edge habitats.

The notable absence of seedlings and sapling within core habitats is most likely contributed to island Torrey pine shade intolerance (McMaster 1980). Leaf litter depth has also been found to inhibit seed bank viability and seedling survival (Hillhorst and Karssen 2000, Jensen and Meyer 2001). Significant core habitats were found in North Grove and Main Gove however core habitat was absent within Cogan Grove. Cogan Grove’s absence of core habitat is likely contributed to several environmental factors.

25 Since the removal of non-native ungulates beginning in 1993, the island Torrey pine has recovered with a current 7:1 juvenile to adult ratio. Areas of most significant recruitment are occurring along the reproductive edge. Seedlings and saplings within these habitats are found in great density likely due to poor seed dispersal. Little is known about the long term effects of this high density intraspecific competition amongst competing seedlings, saplings and parent trees for limited resources. We suggest a further study of this relationship to uncover any potential stress effects on the recent recruitment and reproductive trees within edge habitats.

Soil texture and volumetric water content of island Torrey pine grove soils

Our soil texture analysis (n=24) from a 10cm (4 in) depth resulted in the majority classification of loamy sand (n=11) as the dominate soil type for the Santa Rosa Island Torrey pine habitat (Juma 1999) (Figure 8). Sand (n=8) and sandy loam (n=5) are also notably present across the population (Juma 1999). In 2007, a soil study conducted by the USDA across Channel Islands National Park classified island Torrey pine top soils as loamy sand. Looking at specific groves however results in a slightly different pattern. The USDA analysis of Main Grove (690) typical profile (0-60 in) resulted in gravelly loam (0-5 in), very gravelly fine sandy loam (5-10 in) and bedrock (10-60 in) (United States Department of Agriculture 2007). North Grove (292) typical profile (0-60 in) resulted in fine sandy loam (0-12 in), loam (12-18 in), clay (18-33 in), clay (33 41 in), fine sandy loam (41-45 in) and bedrock (45-60 in) (United States Department of Agriculture 2007). There is no analysis for Cogan Grove.

Field capacity for sandy soil substrates are poor due to large particle sizes resulting in greater cation exchange and more readily flushed macro and micro essential elements (Juma 1999). The island Torrey pine has adapted to these poor sandy soil substrates by developing long taproots at seedling stages (McMaster 1980). Leaf litter is known to inhibit seedling establishment, change soil chemistry and retain or inhibit soil moisture (Putuhena and Cordery 1995, Hillhorst and Karssen 2000). Litter depth is positively correlated with the ability to inhibit or retain moisture due to the adhesive and cohesive properties of water (Putuhena and Cordery 1995). Our linear regression analysis comparing volumetric water content to leaf litter depth was positively correlated in reproductive edge habitats (R2=0.16, p=0.15, n=12) and negatively correlated in core habitats (R2=0.08, p=0.36, n=12) however results were not significant. Leaf litter depth appears to be an inhibitor of soil moisture in core habitats driving soils to be dryer in the dry season (Figure 10). Leaf litter depth is a supporter of soil moisture in edge habitats driving soils to be wetter in the dry season (Figure 9). Our sample sizes are inconclusive of this relationship and only tease out a potential relationship between soil moisture and leaf litter depth across edge and core habitats during the dry season. It is possible that this relationship maybe reversed during the wet season (Putuhena and Cordery 1995). Unfortunately soil sampling access was highly limited across all three groves due to potential disturbance of archeological remains. We suggest a more robust study of the relationship between leaf litter depth and soil moisture across edge and core habitats.

Leaf litter and Precipitation effects on Seedling Germination and Survival

We discovered that leaf litter (Logistic Regression p<0.01), high precipitation (Logistic Regression p<0.01) and the relationship between high precipitation and leaf litter (Logistic Regression p<0.01) are significant for seed bank viability. The effect of leaf litter is clearly seen in low precipitation treatments (Figure 15). Drought conditions without leaf litter result in the poorest seed bank viability (2%) while in the same drought conditions the presence of leaf litter

26 increased seed bank viability (62%). The presence of leaf litter appears to have a similar effect across wet years (64%) and dry years (62%) respectfully. Leaf litter also increases seed bank viability across wet years (Figure 12). There appears to be a limitation to total seed bank viability (64%) in what would appear to be the most ideal environmental condition (Figure 12).

There is no significant difference across treatments and germination rate (Figure 11). Regardless of a wet or dry year in the presence or absence of leaf litter, seeds tend to germinate on a consistent temporal scale (x=49-54 days) (Figure 11). Due to the small sample size of low precipitation without leaf litter (n=1) it is inconclusive if there is a statistical difference between this treatment and other treatments.

There is no significant difference across treatments and seedling survival (Figure 13). Regardless of a wet or dry year in the presence or absence of leaf litter, seedling survival appears to be dependent on other environmental factors. High density recruitment and intraspecific competition for resources maybe a factor contributing to seedling survival in this experimental design (Tiainen et al. 2006). Tray size and depth may have had an effect on seedling mortality. Overall survival was highest in low precipitation with leaf litter (77.4%) followed by high precipitation without leaf litter (68.4%) and high precipitation with leaf litter (62.5%) (Figure 13) Low precipitation without leaf litter had the lowest survival (0%) however, correlations cannot be drawn from this treatment interaction due to its low sample size (n=1) (Figure 15).

In our design, we placed 50 seeds in 1 of 4 trays to simulate the reproductive edge habitat. If seeds were placed in individual pots, results from this study would not be as representative of ecological processes driving areas of significant recruitment. Our experimental design may be subject to some pseudoreplication issues (Hurlbert 1984). Several authors criticize Hurlbert’s limiting pseudoreplication definition and how it is applied to ecological experimental design (Oksanen 2001, Cross 2009). Independent statistical replicates are rarely if ever found in nature and to get around Hurlbert’s definition can be very challenging (Oksanen 2001). Regardless if subjects (seeds) are not considered by definition statistically independent, inferential statistics should always be applied and results should be interpreted by the reader (Oksanen 2001). To remedy this experimental error, we recommend repeating this experiment with 25 seeds/tray with tray sizes reduced by 50% to retain proportional density. We also suggest a larger seed bank of 400 seeds to ensure that each treatment is replicated 4 times. We recommend investigating this density dependent interaction between seeds and seedlings as a factor in an ANOVA analysis. Results from this experiment can then be analyzed for potential correlations. Conclusion

The population at TPSNR may be approaching its carrying capacity given the geographical constraints surrounding the 8 km2 reserve while the SRI population is just beginning to expand beyond its current distribution. The introduction of ungulates to the island damaged habitats while their removal also created a window of opportunity for some species like Torrey pine to establish and increase their population size and area. We found that the reproductive habitat is on the edge of the reproductive population. Soil moisture and leaf litter depth tend to be positively correlated across edge reproductive habitats supporting a significant increase in seed bank viability across wet and dry years. Current expansion of the island Torrey pine population is significant on the edge of the reproductive population under shallow leaf litter. The experiments show that without leaf litter under drought conditions, seed bank viability could be impaired. Non-native ungulate 27 grazing and erosion pressures along edge habitats may have had an effect on seed bank viability in the past. Once a seedling is established, our experiments found that the presence or absence of leaf litter had no significant effect on survival, however shade is the leading cause of mortality. Future studies incorporating this data could project population expansion, habitat limitations, and long-term growth rates Santa Rosa Island is currently experiencing another floral shift, this time it is from the removal of grazers. Our study will continue to monitor this rare species through our demography plots to better understand the life history of the island Torrey pine.

Acknowledgements

We would like to thank Darren Smith of California State Parks for providing the TPSNR data for our comparisons as well as Marcel Koenig, Sean Casey, Clark Cowen, Jim Roberts, Alexis Wallengren, Bree Demarci, Melissa Adylia, Karren Ramirez, John Slagboom, Tyler Nichols, Neil Hammel, Stephen Bednar, Christopher Cogan, Ben Comfort, Reily Pratt, Kyle Burns and Brittany Lucero for contributing to the SRI census data, seed bank and soil collection. We thank the Biology and Mathematics departments for their contributions and continued support to our cumulative study. We would also like to thank the Louis Stokes Alliances for Minority Participation and the National Science Foundation for their financial support. Finally, we would like to thank the Santa Rosa Island Research Station, Channel Islands National Park, and the United States Geological Survey for allowing this study to be conducted.

28 References

Anderson, R. S., S. Starratt, R. M. B. Jass, and N. Pinter. 2010. Fire and vegetation history on Santa Rosa Island, Channel Islands, and long-term environmental change in southern California. Journal of Quaternary Science25 :782-797.

Association, I. S. T., 1999, International rules for seed testing, p. 1-152.

Becerra, P. I., J. L. Celis-Diez, and R. O. Bustamante, 2004, Effects of leaf litter and precipitation on germination and seedling survival of the endangered tree: Applied Vegetation Science, v. 7, p. 253-257.

Biondi, F., D. R. Cayan, and W. H. Berger. 1997. Dendroclimatology of Torrey Pine (Pinus torreyana Parry ex Carr.). American Midland Naturalist138 :237-251.

Center, W. R. C., 2014, Channel Island National Parks Station: RAWS/NDBC Buoy/Manual Ranger Stations, Santa Rosa Island, California.

Coomes, D. A., R. B. Allen, D. M. Forsyth, and W. G. Lee. 2003. Factors Preventing the Recovery of New Zealand Forests Following Control of Invasive Deer. Conservation Biology 17:450.

Cote, S. D., Rooney, T. P., Tremblay, J. P., Dussault, C., Waller, D. M., 2004. Ecological impacts of deer overabundance. Annual Review of Ecology, Evolution, and Systematics 35: 113-147.

Gao, M. 2013. Detecting spatial aggregation from distance sampling: a probability distribution model of nearest neighbor distance. Ecological Research 28:397-405.

Haller, J. R. 1986. Taxonomy and Relationships of the Mainland and Island Populations of Pinus torreyana (Pinaceae). Systematic Botany11 :39-50.

Heusser, L. E. 1995. Pollen stratigraphy and paleoecologic interpretation of the 160-k.y. record from Santa Barbara Basin, Hole 893A. Proceedings of the Ocean Drilling Program, Scientific Results 146, Part 2:265-279.

Hillhorst, H., and C. Karssen. 2000. Effect of chemical environment on seed germination. CAB International, Oxon, UK.

Hurlbert, S. H. 1984. Pseudoreplication and the design of ecological field experiments. Ecological Society of America 11:187-211.Jensen, K., and C. Meyer. 2001. Effects of light competition and litter on performance of Violapalustris and on species composition and diversity of an abandoned fern meadow. Plant Ecology 155:169-181.

IUCN. 2013. Pinus torreyana. A. Farjon, editor.

Jensen, K., and C. Meyer. 2001. Effects of light competition and litter on performance of Viola palustris and on species composition and diversity of an abandoned fern meadow. Plant Ecology 155:169-181.

29 Johnson, M., S. B. V. Wall, and M. Borchert. 2003. A Comparative Analysis of Seed and Cone Characteristics and Seed-Dispersal Strategies of Three Pines in the Subsection Sabinianae. Plant Ecology 168:69-84.

Jonsson, S., B. Gunnarson, and C. Criado. 2002. Drought is the major limiting factor for tree ring growth of high-altitude Canary Island pines on Tenerife. Geografiska Annaler Series A: Physical Geography 84:51.

Juma, N. G. 1999. The Pedosphere and Its Dynamics: A Systems Approach to Soil Science. Salman Productions.

Junak, S., D. A. Knapp, J. R. Haller, R. Philbrick, A. Schoenherr, and T. Keeler-Wolf. 2007. The California Channel Islands. Terrestrial Vegetation of California, 3rd Edition:229-252.

Lombardo, C. A., K. R., Faulkner. 1999. Eradication of feral pigs (Sus scrofa) from Santa Rosa Island, Channel Islands National Park, California Proceedings of the Fifth California Islands Symposium; March 29 - April 1, 1999.

Ledig, F. T., and M. T. Conkle. 1983. Gene Diversity and Genetic Structure in a Narrow Endemic, Torrey Pine (Pinus torreyana Parry ex Carr.). Evolution37 :79-85.

Leopold, A. Grass, brush, timber, and fire in southern Arizona. Journal of Forestry 22:1-10

Livingston, D. S. 2006. Historic Resource Study: A History of the Islands within Channel Islands National Park. Page 917, Ventura, California.

McEachern, A. K., D. M. Thomson, and K. A. Chess, 2009, Climate Alters Response of an Endemic Island Plant to Removal of Invasive Herbivores: Ecological Applications, v. 19, p. 1574-1584.

McMaster, G. S. 1980. Patterns of reproduction in Torrey pine. San Diego State University.

McMaster, G. S., P. H. Zedler. 1981. Delayed seed dispersal in Pinus torreyana (Torrey pine). Oecologia 51: 62-66.

Moody, A. 2000. Analysis of Plant Species Diversity with Respect to Island Characteristics on the Channel Islands, California. Journal of Biogeography 27:711-723.

Nathan, R., F. M. Schurr, O. Spiegel, O. Steinitz, A. Trakhtenbrot, and A. Tsoar. 2008. Mechanisms of long-distance seed dispersal. Trends in Ecology & Evolution 23:638-647.

Nichols, R. V., and G. Spong. 2014. Ungulate browsing on conifers during summer as revealed by DNA. Scandinavian Journal of Forest Research 29:650-652.

Nogales, M., E. Hernandez, and F. Valdes. 1999. Seed dispersal by common ravens Corvus corax among island habitats (Canarian Archipelago). Ecoscience 6:56-61

Oksanen, L. 2001. Logic of experiments in ecology: is pseudoreplication a pseudoissue? OIKOS 94:27-38.

30 Putuhena, W. M., and I. Cordery. 1995. Estimation of interception capacity of the forest floor. Journal of Hydrology 180:283-299.

Raven, P. H., and D. I. Axelrod. Origin and Relationships of the California Flora. Berkeley: U of California, 1978. Print.

Reserve, T. P. S. N. 2013. Protecting the Pines in T. D. Judy Schulman, editor.

Rick, T. C., J. S. Wah, and J. M. Erlandson. 2012. Re-evaluating the origins of late Pleistocene fire areas on Santa Rosa Island, California, USA. Quaternary Research 78:353-362.

Roberts, C. P., C. J. Mecklin, and H. H Whiteman. 2014. American Midland Naturalist 171:219 228

Siepielski, A. M., and C. W. Benkman. 2007. Selection by a predispersal seed predator constrains the evolution of avian seed dispersal in pines. Functional Ecology 21:611-618.

Tanentzap, A. J., D. R. Bazely, S. Koh, M. Timciska, E. G. Haggith, T. J. Carleton, and D. A. Coomes. 2011. Seeing the forest for the deer: Do reductions in deer-disturbance lead to forest recovery? Biological Conservation 144: 376-382

Thompson, and West. 1883. History of Santa Barbara County, CA, Oakland, CA.

Tiainen, M., P. Jyrki, R. Julkunen-Tiito, and H. Roininen. 2006. Intraspecific competition, growth, chemistry, and susceptibility to voles in seedlings of betula pendula. J Chem Ecol 32:2287-2301.

United States Department of Agriculture, N. R. C. S. 2007. Soil survey of Channel Islands National Park, California.

Vander Wall, S. B., and J. W. Joyner. 1998. Secondary dispersal by the wind of winged pine seeds across the ground surface. American Midland Naturalist 139:365.

Wells, M. L., and A. Getis. 1999. The Spatial Characteristics of Stand Structure in Pinus torreyana. Plant Ecology 143:153-170.

Williams, A. P., C. J. Still, D. T. Fischer, and S. W. Leavitt. 2008. The Influence of Summertime Fog and Overcast Clouds on the Growth of a Coastal Californian Pine: A Tree-Ring Study. Oecologia 156:601-611.

Williams, C. E., M. V. Lipscomb, W. C. Johnson, and E. T. Nilsen. 1990. Influence of Leaf Litter and Soil Moisture Regime on Early Establishment of Pinus pungens. American Midland Naturalist 124:142-152.

Zavarin, E., W. Hathaway, T. Reichert, and Y. Linhart. 1966. Chemotaxonomic Study of Pinus Torreyana Parry Turpentine. Phytochemistry6:1019-1023.