The future of our wind farm sites looks like this.

It’s been a busy couple of weeks!  First, a new CLM intern has joined the Windy Bugs crew – Laura Super.  We have been introducing her to our field sites and Laramie.

Laura Super (L) and I near our camping site.

It is really drying up around here.  While we’ve had some rain and hail in Laramie, our Choke Cherry site was so dry that our floral surveys were VERY easy this trip.  We did collect lots of bees and other insects, and saw one beautiful milkweed.

Aaron equipped with cyanide tubes and a funnel

Last weekend, I had the opportunity to go on a short birding trip with WYNDD ornithologist Michael Wickens.  We went into the Snowy range near Medicine Bow peak.  It was absolutely gorgeous and a great chance to see some different Wyoming landscapes, insects, and birds.  Since my bird ID skills are pretty much non-existant, it was great to be with an expert and see how bird point counts are done while trying to learn some songs and calls.

Michael Wickens listens for birds in a meadow

I was fortunate enough to see a number of interesting birds, including three-toed woodpeckers, mountain chickadees, a ruby-crowned kinglet, and grosbeaks.  Since the mountains are much wetter than the sagebrush-dominated areas I work in, there were many more visible arthropods out and about.

A wood tiger moth (Parasemia plantaginis)

A Syrphid fly

Cuckoo wasp (Chrysididae)

A female wolf spider (Lycosidae) with an egg sac

The wildlife on this trip was certainly exciting, but the plant life was amazing as well!  I got to see two native orchids, a beautiful bright pink Castilleja, Columbines, and some lovely alpine plants.

Parasitic orchid Corallorhiza maculata

Platanthera dilatata, another native orchid

Castilleja rhexifolia

I had such a wonderful time in the Snowies, despite the mosquitoes, that I plan to go camping and hiking there next weekend.  Before that, we’re headed back to our Sierra Madre site tomorrow morning!

After a well deserved vacation involving a trip back home to Chicago, an ArcGIS course and a wedding (not mine); I find my self getting ready to return to work. Having just finished that ArcGIS online course I have been spending my free time trying to get my hand on any and all books that could enlighten me on even more creative uses of this program for biologists. With all this new found knowledge I have gained I am ready and anticipating a new project.  Upon returning to the office, my project is set before me! The next question is, can I do it?

At first my heart plummets as the project is explained to me. The sudden drop my heart does is not due to disappointment with being assigned a boring project, or even one that doesn’t related to my interest, the plummet my heart takes is caused by the intensity of the project. The project is exactly what I wanted, an outlet to try my newfound knowledge in ArcGIS and continue expanding my repertoire of R commands, but now sitting in front of my mentors, the task seems overly daunting. The explanation is peppered with statistical and technical terms I have never heard of and requests to “write an application” figure out the best algorithm”, and “obviously make sure to statistical analyze your models using an AIC”. As the mentors leave with promises of getting me a few papers and the data sets, I sit there in shell shock. The world is spinning around me.  Doubt slowly creeps in, the fear of failure blinds me. I take a deep breath. Focus. I’ve got this.

This brings me to a small tangent. BIOLOGISTS NEED MORE MATH in their training. I know that oftentimes students get to choose some of the courses and one could specialize in math, but what about the core courses? I do not particularly like math, but as I am working on different projects as an ecologist I have been reminded how essential truly understanding statistics is to experimental design. Statistician and GIS professionals are good at what they do, but oftentimes don’t seem to be able to grasp the underlying biological concepts to be to too much use to biologist. So, in essence, I think that this is just my little wake-up call to each and everyone of you to become a stronger biologist by solidifying an intimate knowledge of statistics, modeling and programming. I did not think I would be going back to school (I just finished my Masters), but it seems that this intership might have gotten me super stoked about ecological modeling. Any good programs you guys can recommend?

Anyway, my mentor soon returns with a thumb drive loaded with all sorts of goodies. Welcome back!, The equivletant of 3 to4″ inch manila folders filled with reading and data sets gets thrown on my desk.

The key, and hardest parts to succeeding at this project is starting. With that in mind, I start out with determining what exactly AIC actually stands for and how do I use it to analyze my models.

With the help of The R coding Hand book and Wikipedia (oh, how students I TA’d would love to yell at me for this as I once did to them) I compiled a little fact sheet about AIC curves

I do not expect this to be very useful to you guys but since I wrote it out for myself I figured I would not be selfish and share it.

 AIC Definition, History and R coding

The Akaike information criterion also known as AIC is a measure of the relative quality of a statistic model for a certain set of data. It is, more officially a “statistic trade as a penalized log-likelihood”. It looks at the complexity and goodness of fit allowing a means for model selection. It is important to remember that this criterion can not test a hypothesis or provide an absolute test telling us how good the models fit the data; it just tells you which ones fit better. It was published in 1974 by Hirotuga Akaike; this was in Japanese and was not widely known. Only in 2002 was it published in English by Burhams & Anderson.

The AIC is:

K=#of parameters in model

L=max value of likeligood function for the models

 *Best models is the one with the lowest AIC, and simple is better ( too many parameters in an equation is penalized while goodness of fit is sought after)

**Only used with large sample sizes (number of models) there is a correction if you want to correct for a finite sample size(AICc)

In practice once you have calculated the AIC criterion for your models then you have to decide which ones minimize the amount of data you lose. This is done by looking at the relative probability of the model in question minimizing information loss, aka ((AICmin-AIC)/2).

R CODING 

#Getting AIC

Data<-read.table(“—–”, header=T)

attach( data)

name(data) # the names are growth and tannin, lets pretend

model<-lm(growth~tannin) #this is to work out the linear regression model for this data in R

#now to define all the variable in the equation

N<-length (growth)

sse<- sum((growth-fitted(model))^2)

s2<- sse/(n-2)

s<-sqrt(s2)

            #computing log likelihood

-(n/2)*log(2*pi)-n*log(s)-sse/(2*s2)

#not to calculate the AIC, -2* loglikelihood+ 2(p+1)

-2 *(insert your loglik number)+ 2(number of parameters+1)

# Once you have this the AIC you want to compare them to each other

model.1<- lm(Fruit~Grazing*Root)

model.2<-lm(Fruit*Grazing*Root)

AIC(model.1, model.2)

#if you have more than two models you do this:

models<-list(model1, model2, model3, model4)

aic<- unlist (lapply (models,AIC) #this extracts the aic, aic will be a vector in which you can search for the minimum.

More on this project to come. See you next time! That is, if the monsoons do not wash me and my computer away.

7/16/2013

Hello again from Dillon, MT. I cannot believe that it has already been a month since I last posted. Time is really flying, and I am grateful for the time spent here. My mentor and I have been kicking butt and establishing tons of upland and riparian trend monitoring within the Medicine Lodge watershed on our district. The monitoring is recommended based on the results of an environmental assessment completed on the watershed. Most monitoring is riparian related and based on the outcome of the Proper Functioning Condition stream assessments (or PFC). If a stream is rated as lower than PFC, (Nonfunctioning or functioning at risk) management changes are put into place in an attempt at restoring the riparian and spring areas. Some management changes I have seen involve the construction of a fence or spring exclosure, which usually keeps cattle, and not wildlife out of the area. Sometimes if the manager sees fit, a spring will be developed to support a water trough which directs cattle away from the riparian areas, but also provides a steady supply of drinking water. Pasture rest rotation or shorter grazing cycles can be another management change that gives the area time to heal over the growing season. Trend monitoring is another way to monitor grazing allotments and see change over time before having the need to implement more strict management changes. When deciding these management changes, the resource managers must work with grazing permitees.

I am really happy to be working for this district, because they put a huge emphasis on the importance of watershed management and the proper care of riparian areas. My next task will be completing Montana Riparian and Wetland Assesments (MRWA) which also relates to updating rangeland EAs. A lot of camping and stream walking is involved in completing MRWAs. Other than that, I am really enjoying the scenery and looking forward to starting graduate school at Oregon State University in the Fall. Until next time,

Grace

Dillon, MT 

Going from one of the muggier parts of the country to one of the driest has been one of the more dramatic transitions that I’ve experienced since starting my internship here at the Bishop BLM—not that I’ve had much time to process it. It’s hard to believe that I’ve already been here for three weeks…or is it hard to believe that it’s only been three weeks? Coming in at the height of field season has made for a hectic—and exciting—first month on the job, and I’ve been having a blast.

As someone who has spent most of her life within ten hours of the East Coast, shrub diversity was never something I paid much attention to (not with so many interesting trees overshadowing their diminutive counterparts). Here in the scrublands, however, shrubs rule supreme, and I have spent a lot of time these past few weeks learning to distinguish between bitterbrush and sagebrush, wax currants (Ribes cereum) and desert gooseberry (Ribes velutinum), horsebrushes and rabbitbrushes (not to mention rabbitbrushes and rabbitbrushes). Especially interesting is spiny hopsage (Grayia spinosa), a medium-sized shrub that is found throughout Eastern California. The showiest parts of the plant are not its flowers, but rather the seed-bearing bracts—small, colorful structures that look like a cross between a petal and a leaf. In the spring, the bracts are bright pink; as they dry, they turn yellow and crispy. And as the first plant that I collected seeds from for SOS, hopsage is definitely one of my favorite plants to run across in the field.

The most challenging shrub identification task we have to tackle on a regular basis is teasing apart the different sagebrushes. Distinguishing between low sagebrush (Artemisia arbuscula) and smaller big sagebrush individuals (Artemisia tridentata) can be tricky, but it gets especially complicated when you try to separate out the three subspecies of big sagebrush: big basin sagebrush, Wyoming big sagebrush, and mountain big sagebrush. And did I mention that they hybridize? But it turns out that these distinctions matter, and not just to someone interested in taxonomy. These subspecies are chemically distinct, and it makes a difference to the nesting sage grouse that use these shrubs as both shelter for their nests and a critical food source during nesting season. This is one of the coolest parts of my job—getting to work on a variety of projects, most of which depend on each other in some way and really get at the interactions between animal species of interest and the plant communities that they depend on.

Sage grouse nest in a hopsage bush

Until next time!

We sampled insect traps to assess the diversity  of insect pollinators. Above shows Aaron and Sadie checking the traps.

Nearby the insect traps, our team searched in quadrats for open flowers. Often, however, the sampled quadrats did not have many flowers in bloom at this dry time of year.

After collecting in the field, we spent time in the lab processing insect samples and pinning. Shown under the microscope, here is an Agapostemon sp. that I pinned.

Before pinning, insect samples from the field were sorted, dried, and cleaned. For each sample, insects were carefully removed from filter paper onto a white sheet of paper (for constrast). Forceps, a paintbrush, and a hand lens were useful tools for processing.

Here are some pinned insects with the sample tags. The pinned insects are beautiful to look at, and important for science — but, for many reasons, I definitely prefer living insects over pinned ones.

The past few weeks have been super productive here in the Buffalo Field Office. My SOS coworker Nick and I have so far completed 18 collections and in doing so have honed our GPS abilities, rancher communications, and knowledge of Wyoming grasses and seed ripeness. I’ve gotten completely lost, but thankfully found my way back, and have been working so hard I’m exhausted everyday I return to the office. But it’s the best kind of internship I could ask for.

Besides seed collections, I got the amazing opportunity to hike with some BLMers and people from the University of Wyoming into the Gardner Wilderness Study area near Barnum. The first day we did limber pine monitoring in the area looking for rust, adelgids, and overall health. The second day, the recreation planner and I embarked on the most epic hike of my life. Literally nothing could prepare me for the hike it was. Imagine looking at a cliff face and thinking “there’s no way anyone could ascend that” and then realize that you will have to, and you must find a way. We hiked for 10.5 hours (only 8.3 miles) mapping the route and looking for any public activity. We hiked down a dry creek, alongside bear trap creek, up a steep drainage (with some skilled rock climbing) of a canyon and back down, alongside more of bear trap creek and back up the other side of the canyon through prickly bushes to our camp. We came across breathtaking views and a couple mountain lion dens where I found an awesome elk skull with a five point rack. I returned to the office today scraped up (my legs look like the product of Freddy Kruger) and extremely sore, but also very proud of myself and gained another awesome experience with my coworkers and the BLM.

-Kelly Thomas

We have changed gears and focused our efforts towards beautifying our office. The landscapers hired to plant flowers and grasses around the office didn’t exactly put their best foot forward, to put it nicely. As a result, most of the plants died leaving the office with barren, dry, dusty soil. So Sheila had the idea to create native flowers and pollinator garden beds. These last 2 weeks have been dedicated to building said beds. This project was a nice reprieve from collecting seeds. I got a chance to get back to the activity I love to do: garden. I had forgotten how much I loved it actually. Jacob, Sheila, and I didn’t do all of the work. We have to give many thanks to the Youth Conservation Corps guys for their tireless efforts in helping us lay rock around the beds and build trails around the office.

Putting the finishing touches:

Fourteen tons of rock from Arizona, 2.5 truck beds of mulch, and over 170 native plants later here is the finish product: