DOI: 10.7280/d1bt46
title: Sentenac Cienega wildlife and vegetation data

description: Sentenac Cienega is a degraded wetland ecosystem in Southern California’s
 Anza-Borrego Desert State Park. Recently, researchers have taken an
 interest in the conservation and restoration of this Cienega, and it is in
 accordance with this goal that we performed our work. This project had
 four major components: a wildlife monitoring protocol to determine species
 richness and relative abundance, a greenhouse drought/salinity resilience
 trial, in-field plant transplantation trials, and a survey of vegetation
 composition throughout the entire area. The wildlife monitoring project
 results indicate that wildlife activity is highest in areas with easily
 accessible food, water, and routes for transportation. The greenhouse
 trial indicated that soil moisture levels had the greatest effect on the
 growth of Juncus mexicanus, while salinity levels had the greatest effect
 on the relative growth of Anemopsis californica. Mortality was very high
 in our field transplantation trial, with all plant species exceeding 90%
 mortality across all planting plots. This mortality was likely due to a
 combination of herbivory and drought effects. Vegetation composition
 mapping results show that the species richness of native species is higher
 than that of non-native species but two-thirds of the area is dominated by
 non-native species. There is a strong positive correlation between native
 and non-native richness and a strong negative correlation between native
 and non-native cover.
description: Eight total camera traps (Browning DarkOps Elite HD Model
 BTC-6HDE) were placed throughout Sentenac Cienega from November 2020 to
 April 2021 (Figure 4). Various areas to scout were chosen based on a map
 of known GPS tracking data locations of collared lions from a prior
 unrelated, unpublished study (Figure 5). This was done to heighten the
 chance of mountain lion image captures, as well as create a baseline for
 scout-worthy locations considering that wildlife had been seen in these
 areas at one time. A map of potential locations for cameras was created
 using ArcGIS Online. Scouting was done in November 2020 over a two-day
 period and consisted of finding signs of animal tracks, trails, beds,
 herbivory, scat, and carcasses. Areas with several signs of wildlife
 activity, as well as locations that appeared attractive to wildlife within
 varying microhabitats and vegetation zones, were ultimately chosen for
 camera installation. This was to ensure we would capture as many different
 species as possible to determine species richness, as well as areas with
 high animal activity frequency.  We established eight
 cameras throughout the cienega: SC1 and SC2 in Riparian Wash- East, SC3
 and SC4 in Willow Woodland, SC5 in Marsh to Upland Transition Zone, SC6 in
 Bridge Wash- West, SC7 in Bridge Wash- East, and SC8 in Remnant Mixed
 Riparian Zone (Figure 4). Due to possible extreme weather conditions, SC1,
 SC7, and SC8 were relocated in January 2021 near their original locations,
 but with different angles, slopes, and heights. Therefore, they were then
 renamed and treated as separate cameras. SC1, SC7, and SC8 captured images
 from November 2020 to January 2021. SC1 became SC9, SC7 became SC10, and
 SC8 became SC11. These three cameras captured images from January 24, 2021
 to April 7, 2021.  During camera installation, we
 attached cameras to either a metal post, tree, or fence that appeared
 stable enough to house a camera. All cameras were run continuously from
 the time they were installed until we stopped collection data or a camera
 was moved, which ranged from 68 days (SC7, SC8), 69 days (SC1), 74 days
 (SC 9, SC10, SC11), and 141 days (SC2, SC3, SC4, SC5, SC6). Cameras were
 attached between heights of 4 cm to 80 cm (depending on location, slope,
 and angle) and set to take three consecutive shots with 60-second delays
 in between camera triggers.  During photo processing,
 we extracted data consisting of time and date, species, number of animals
 and species per photo, directionality, and camera location. These data we
 entered on several Google Sheets, which we compiled in R for further
 analysis.  Within R, the total number of individuals
 for each species in a 30-minute were tallied for each camera location (SC1
 to SC11) across all dates. From the master file compiled in R and
 excluding birds, humans, and domestic dogs, we determined the species
 richness at each camera location and across the entire cienega, the
 relative abundance index (RAI) of each species (measured as the total
 number of unique species divided by the duration the camera collected
 data) at each camera, and the RAI of overall activity at each camera
 (measured as the total number of days the camera captured activity over
 total active camera days).  The subjects of our
 greenhouse drought and salinity tolerance experiment were two plant
 species native to Sentenac Cienega, Juncus mexicanus and Anemopsis
 californica. Three levels of water and salinity treatments were applied to
 the plants, combined for a total of nine different treatments for both
 species.  After harvesting similarly-sized rhizomes of
 each species in the field, we transported them to the UCI greenhouse and
 potted them in one-gallon nursery containers filled with custom potting
 mix. This potting mix (2 parts pumice: 2 parts redwood compost: 2 parts
 peat moss: approximately 0.5 parts sand) has previously been used by UCI
 researchers to grow coastal sage scrub plants with good
 results.  The water treatments had three levels: low,
 medium, and high. These treatments were designed to simulate field
 conditions under varying levels of precipitation. The low water treatment
 was designed to maintain potting mix moisture in line with the lowest soil
 moisture in the field (5-10%), the medium treatment was designed to
 maintain potting mix moisture near the average soil moisture in the field
 (20-25%), and the high water treatment was designed to maintain potting
 mix moisture in line with the highest soil moisture at Sentenac Cienega
 (45-50%). The salinity treatments also had three
 levels: control, low, and high. The control treatment was intended as a
 base comparison for the other treatments. The low treatment was determined
 by averaging the conductivity levels found at the cienega, and the high
 treatment was determined by increasing the highest salinity level found at
 the cienega by one-third. Treatments were applied by initially irrigating
 each potted plant with one liter of treated DI water. The control salinity
 treatment was applied by irrigating plants with untreated DI water. The
 low salinity treatment was applied by irrigating plants with DI water
 salinized with table salt (NaCL) to a conductivity of 3-4 millisiemens/cm.
 The high salinity treatment was applied by irrigating plants with DI water
 salinized to a conductivity of 11.5-12.5 millisiemens/cm. All saline
 solutions were measured with an Oakton PCD650 calibrated to a solution of
 10 millisiemens/cm.  Prior to starting the greenhouse
 experiment, we conducted a soil water capacity experiment to determine the
 watering schedule. First, we took the weight of three empty pots, then
 added potting medium to the pots and took the weight of the potting medium
 plus the pots. Next, we watered the pots to excess and waited 30 min for
 the pots to drain until the three pots reached constant weight. After the
 pot weights stabilized, we took the total weight of each pot (potting mix
 + water + pot). We continued to take the total weight of each pot daily,
 recording the downward trend of the soil moisture, until the soil moisture
 reached the lowest level in the field (under 10%). Based on the results of
 this soil water capacity experiment, we determined that the high water
 treatment would be irrigated with 120 ml of water every four days
 beginning eight days from the start of the experiment; the medium water
 treatment would be irrigated with 120 ml of water every four days
 beginning 18 days from the start of the experiment; and the low water
 treatment would be irrigated with 120 ml of water every four days
 beginning 28 days after the start of the experiment. This irrigation
 schedule would keep the soil moisture levels constant and within the
 correct treatment range over the course of the experiment. 
 After being allowed to acclimate to the greenhouse environment
 for a month, treatments were started at the end of January. Data was
 collected weekly until the experiment ended mid-April. Plant biomass was
 measured differently per species as appropriate. A. californica growth was
 estimated by measuring the number, length and width of green leaves, as
 well as noting any stolon growth/offsets produced by the plant. J.
 mexicanus growth was estimated by counting stems and measuring their
 height.  To determine how salinity had changed over the
 course of the experiment, we analyzed the electrical conductivity (EC) of
 the potting medium using a pour-through technique (Nemali, 2018; Appendix
 C). This technique measures the EC of a leachate solution as a proxy for
 how much soluble salt is present in the growing medium. To perform the
 pour-through method, we grouped J. mexicanus plants by treatment, then
 irrigated thoroughly using tap water. After an hour, we poured 120 ml of
 DI water into each pot, collecting the leachate from each treatment group
 into one bucket. We then measured the EC of that leachate to obtain our
 result. The field transplantation experiment was
 modeled after a similar experiment performed by UCI researchers in 2018,
 and made use of the same plots established for that experiment. Ten plots
 were laid out across the cienega, situated to capture the environmental
 gradient present onsite (Figure 6). We chose three native species,
 Anemopsis californica, Juncus mexicanus and Distichlis spicata as our
 target species. On the morning of transplantation day, we harvested
 rhizomes of each species from previously identified donor sites. In each
 plot, we planted four individuals per species, totalling 12 individuals
 per plot. In areas with hard, dry soils, soil was loosened to maximize
 root contact with soil and prevent “root boundedness.” We flagged all
 transplants and watered them well, with plots 1-4 receiving four gallons
 each of supplemental irrigation and plots 6-10 receiving two gallons each
 of supplemental irrigation. Rough terrain and a tight schedule prohibited
 us from irrigating all 10 plots with four gallons.  
 After transplantation, we visited the site twice for data
 collection. We noted whether individuals survived, the number of any green
 leaves, and the maximum height and width of each surviving
 individual.  We conducted our vegetation mapping using
 spatial information captured by Survey123 (2021 Esri 3.12.277) on cell
 phones. We walked across the site and when there was a change in the
 dominant species, we drew a polygon on the map. Within each polygon, we
 collected all the present species and their estimated percent cover. The
 name of each polygon was the dominant species code (a combination of the
 first three characters of the scientific name, e.g. the code for Anemopsis
 californica is ANECAL), number of the dominant species occurrences, and
 the date (e.g. BASHYS_1_022421). For the percent cover, we set five levels
 in increments of 20, from 1 to 100 (e.g. 0-20, 20-40, etc.)  We estimated
 the percent cover by the area of each polygon and the species distribution
 within the polygon. All other data was also recorded on standard paper
 datasheets. Data from the field survey was uploaded to ArcGIS Online at
 the end of each data collection day, checked for quality and consistency,
 and prepared for use in the mapping process.  Mapping
 was done using ArcGIS (Esri ArcMap 10.7.1). Since the data were collected
 over multiple days, there are several different layers of the vegetation
 polygons. We downloaded the layers from ArcGIS Online and opened them in
 ArcMap. We used the merge tool to merge different layers into one layer.
 Then we used the reshape feature tool and edit vertices tool to make the
 boundaries of the polygons coincide. We used graduated symbols to show the
 native and non-native species richness. To show the distribution of native
 and non-native species, we used graduated colors to represent the species
 percent cover trend across the site. We also used different colors to show
 specific dominant native and non-native species of different alliances.
 Finally, we finished the maps by adding the appropriate legend, North
 arrow, scale bar, and title. To further explore the
 relationship between native and non-native species richness and coverage,
 we used R (R Core Team, 2019) to analyze if there was any correlation
 between native and non-native species richness and percent cover. A
 Shapiro-Wilk test was done to see if the variables were normally
 distributed. We ran the Pearson's test because the four variables
 were not normally distributed. Finally, we visualized the data by creating
 a scatter plot and a corresponding trendline to show the correlation
 between native and non-native species richness and percent
 cover.
description: ReadMe file is uploaded as a .txt file named README_Capstone