GEOG 566






         Advanced spatial statistics and GIScience

Archive for June, 2018

June 11, 2018

Analysis of flowering phenology as a step towards understanding phenological synchrony

Filed under: 2017,Final Project @ 5:55 pm

BACKGROUND: While the cinnabar moth (Tyria jacobaeae) was intentionally introduced to North America as a biological control insect, its release had unintended consequences as it established on a non-target native perennial herb, Senecio triangularis (Diehl and McEvoy, 1988). Populations of triangularis colonized by the cinnabar moth can experience heavy foliar herbivory (up to 100%) without […]

Exploring historical constraints on fire across the Central Oregon Pumice Plateau

Filed under: 2018,Final Project,Final Project @ 5:45 pm

Question My original question was how historical fire occurrence varies spatially on the central Oregon pumice plateau. My question morphed into how did constraints on fire including climate, fuel abundance and continuity, and lodgepole pine forest influence the occurrence of fire. Dataset My dataset consists of records of fire occurrence for 52 sample points distributed […]

Negative relationship between transect movement through species-space and substrate heterogeneity

Filed under: Final Project,Tutorial 3 2017 @ 4:32 pm

Questions First, to gain a better understanding of the relative heterogeneity in slope angle among sites, I reexamined the cumulative spatial buffers of benthic bathymetry, and calculated non-overlapping ‘donuts’ of expanding space around each site, Mirroring tutorial 2, I then recalculated slope angle minimum, maximum, mean, and standard deviation. Next, I expanded off multivariate analyses […]

Assessing the importance of 3 predictors of fire occurrence and the random effect of site with a GLMM model

Filed under: Exercise/Tutorial 3 2018 @ 4:11 pm

Question The question I asked was whether fire occurrence from 1700-1918, a binary (0 – no fire, 1 = fire) response, was related to three explanatory variables: Climate – Annual Palmer Drought Severity Index (PDSI) a measure of moisture stress reconstructed from tree rings (range -6.466 – 7.234; severe drought to cool and wet). In […]

Exploring recreational movement behavior through hidden Markov models

Filed under: 2018,Final Project @ 3:55 pm

Research Question Asked Glacier Bay National Park and Preserve (GLBA), located in southeast Alaska, contains over 2.7 million acres of federally designated terrestrial and marine wilderness (National Park Service, 2015). Recreation users access GLBA Wilderness primarily by watercraft; the park lacks formal trail networks in its wilderness and terrestrial connectivity is fragmented by the park’s […]

Modelling snow for sheep

Filed under: 2018,Final Project @ 1:21 pm

RESEARCH QUESTION – How do seasonal snow conditions affect Dall Sheep recruitment? Dall an emblematic species of alpine regions in high latitude North America. Their ranges extend from the mountains of the Yukon Territory, Canada, to the furthest western extent of the Brooks Range in Alaska. Populations of Dall Sheep have declined 21% range-wide since the […]

Considering Beaver Dam Occurrence based on Stream Habitat and Landscape Characteristics

Filed under: Final Project @ 1:18 pm

Research Question Q1: How does the Suzuki and McComb Habitat Suitability Index (HSI) relate to observed beaver dams and the West Fork Cow Creek drainage?  Q2: What other factors explain the selection of suitable habitat?  At the beginning of this effort, the question I was most interested in was “How well does the Habitat Suitability […]

The Hidden Behavioral States May Still Be Hidden: Exploring the Applicability of Hidden Markov Models and Environmental Covariates for Modeling Movement Data (Exercise 3 Part 2)

Filed under: 2018,Exercise/Tutorial 3 2018 @ 10:10 am

Question Asked Overall, my aim for Exercise 3 work was to determine the extent to which environmental covariates (of the type explored in Exercise 2), could be related to spatially explicit behavioral states defined by step length and turning angle data generated from GPS tracks of movement in Exercise 1. As described in my Exercise […]

Using correlation-based techniques to investigate population trends in Bull Kelp (Nereocystis luetkeana) in southern Oregon

Filed under: Final Project @ 9:52 am

The Question: I was initially looking to explore correlation between a kelp canopy coverage data set and a suite of environmental variables. My question morphed into examining the correlation between canopy cover and two temperature data sets. The Data: I used three datasets to investigate this question. The first was a 35-year time series of […]

June 10, 2018

Fitting Distributions for Two Spatial Data Behavioral Measures: Step Length and Turning Angle (Exercise 3, Part 1)

Filed under: Exercise/Tutorial 3 2018 @ 10:11 pm

Question Asked For Exercise 3, I wanted to explore the degree to which two environmental covariates influence the transition probabilities between and among two behavioral states using a hidden markov model approach. To operationalize the behavioral states, paired step length and turning angle measurements were generated from the raw GPS tracks, as described in my […]

Logistic Regression of Plant “Vulnerability” Against Three Explanatory Variables

Filed under: Exercise/Tutorial 3 2018 @ 3:46 pm

QUESTION: In this exercise, I used logistic regressions to investigate whether whether three explanatory variables (growing degree days, soil temperature, soil moisture) could be related to changes in the probability of finding vulnerable versus invulnerable plants in my 2017 data. Logistic regressions allow us to fit models to data of probabilities that range between 0 […]

June 9, 2018

Relationships between environmental features and recreationist behavior in Grand Teton National Park

Filed under: 2018,Final Project @ 7:12 pm

The research question that you asked. Broadly, my research question at the beginning of the course was: “what spatial and temporal patterns emerge from day-use hikers in Grand Teton National Park?” I appreciated starting out with a broad, exploratory question as it allowed me to think creatively and learn a variety of approaches for analyzing […]

June 8, 2018

Interannual variation in phenology and productivity at a C3 and a C4 grassland

Filed under: 2018,Final Project @ 12:48 pm

1. Research question Introduction Climate change is altering the production and distribution of plant species (Kelly & Goulden, 2008); however, the response of grasses to climate change is relatively understudied compared to woody plants, especially in tropical regions (e.g., Schimel et al. 2015). Globally, grasslands and savannas are estimated to comprise 30 percent of non-glacial […]

June 7, 2018

Wavelet and Cross Wavelet Analyses of Kelp Canopy Cover and Temperature

Filed under: Exercise/Tutorial 3 2018 @ 4:26 pm

Question: With this exercise I wanted to look at patterns in the cycles of temperature and kelp coverage in southern Oregon. I wanted to examine if these two variables fluctuate together and if they do, is that synchronization is constant throughout the timeseries. Tool: To do this I used wavelet analysis and cross wavelet analysis. These analyses […]

Aggregating Suitable Dam Habitat to Consider the Role of Habitat Size and Connectivity

Filed under: 2018,Exercise/Tutorial 3 2018 @ 11:47 am

Question: How does the size and connectivity of beaver dam habitat relate to observed dam sites in West Fork Cow Creek? Approach: In Exercise 2, I considered if stream gradient, active channel width, and valley bottom width, described by Suzuki & McComb (1998) as the most important predictors of beaver damming, corresponded to the observed […]

June 6, 2018

Exploring the relationship between floating guidance structures, hydraulics, and the location of behavior changes in fish

Filed under: Final Project @ 7:43 pm

Question, dataset, and approach: This research investigated the hydraulic and behavioral impacts of a floating guidance structure in an experimental channel on juvenile Chinook salmon. Three exercises were conducted to determine if any relationships exist between channel hydraulics (which were stationary, measured at discrete locations and interpolated to become spatially-continuous) and the locations of behavior […]

Geographically weighted regression and the location of behavior changes

Filed under: Exercise/Tutorial 3 2018 @ 6:07 pm

Question: Exercise 2 determined that velocity gradient, water speed, and turbulent kinetic energy (TKE) gradient are the most important aspects of principal components that predict the spatial distribution of behavior changes. However, because channel hydraulics vary on a small scale (e.g. centimeters) within the experimental channel, the relationship between each hydraulic variable and the location […]

Observed vs. expected time spent in vegetation types as a function of distance to water

Filed under: 2018,Exercise/Tutorial 3 2018 @ 10:32 am

Disclaimer – this post is long, particularly in the ‘steps taken’ section. I may use some of these methods in the Fall, so I made it very detailed. Question asked For this analysis I wanted to dig a little more into the relationship between vegetation type, distance to water, and the movement of the recreationist. […]

June 5, 2018

Comparing SnowModel output to metrics of Dall Sheep recruitment.

Filed under: 2018,Exercise/Tutorial 3 2018 @ 4:16 pm

Question asked Is Dall Sheep recruitment more influenced by near-summer snow conditions or do early snow season conditions also play a role? A typical metric for assessing sheep recruitment, i.e. the number of young animals available to ‘recruit’ into the population, is the lamb to ewe ratio (hereafter referred to as lamb:ewe). In the case […]

June 4, 2018

Shift in the lag of GPP with soil water content at a C4 grassland site

Filed under: 2018,Exercise/Tutorial 3 2018 @ 4:48 pm

1. Question asked: How is soil water content related to gross primary production (GPP) and the light use efficiency of photosynthesis (LUE) of a natural grassland? How do these relationships differ between C3- and C4-dominated grasslands? Specifically, how does interannual variation among water years? 2. Tool / approach used: To answer this question, I calculated […]

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