When Nature Calls

 When Nature Calls

by

Tomas Jimenez

Figure 1. Arrival at Montana de Oro

Day two of data collection started off much better than the first. Well rested, hydrated, and with plenty of time for breakfast spirits were high for this eucalyptus enthusiast. Upon arrival, we quickly split into two teams: The Alpha team (Jefferson and Nathan) and the B team (Tomas, Nick and Adam). What we lacked in raw talent we made up for with scrappy determination. Although we were the underdogs, we would not be discouraged. We quickly counted two randomly selected circular areas using our three man counting method. Adam and I would walk out fifteen meters from Nick to act as markers. Nick used his excellent tree counting ability to count the trees within the section of the circle that Adam and I marked off. We would then rotate around the circle to count the next section, and so on, until all the trees in the circle were accounted for. 

Figure 2. Adam acting as a marker or a bouncer in the woods

At this point, against all odds, we were beating the A team, until the unthinkable happened. My big, beautiful breakfast that I had been so grateful for was about to turn on me. Nature was calling in a way that it had never called before. Panic overcame me. With no known toilets around, few good wiping leaves, and a wildlife ecology group that found it "funny" to harass me at my most vulnerable. I searched frantically through the woods for the smallest sign of hope, until finally I stumbled upon a small wooden outhouse. All was saved! I'm not sure what good I had done in my life to deserve to find this beautiful outhouse and I didn't care. In that moment everything was right in the world. All my problems blissfully dissolved away into thin air.

Figure 3. Catharsis 

Unfortunately, things weren't all that they seemed. Once I figured out how to close the door everything was going smoothly until one of my companions through a large tree branch at my humble sanctuary. It made a loud noise which startled me, but it didn't startle me nearly as much as what the noise caused. Out of every nook and cranny of the old wooden hut, came every type of creepy, crawly critter that you could imagine. The bugs coated the inside of the walls completely surrounding me. If that weren't enough there was an odd scratching noise from outside the outhouse that sounded like something out of a horror movie. When I tried to open the door I found that my fellow teammates had wrapped the transect around the bathroom a couple times to trap me. Eventually they let me out and we counted trees.

Fin.

Figure 4. The B team (aka team T.A.N) after hard day's work

B Squad

Team TAN

Team 1 set out for Montaña de Oro in the hopes of finally gathering some concrete data. We sat down the previous week and discussed what went wrong with our initial sampling and how to adjust our technique. We made several changes, which have been discussed in previous posts. One of the key changes to our methodology was breaking up into separate groups. Alpha Team, consisting of Jefferson and Nathan, set of on their own to gather a smaller sample of data because they were only a tandem. The team consisting of myself, Adam and Tomas, affectionately named Team TAN gathered a slightly larger data set.

Data Collection Can Get a Little Messy

Testing out our new data collection methodology excited us all. The data came fast and furious as we worked at a fever pitch. We had to be careful though, because when you're sciencing as rapidly as we were, things can get out of control quickly. One of our transect tapes got entangled with a tree, it was an utter and complete disaster. We were uncertain if we could recover from the tragedy. Team TAN buckled down and persevered though, we would not be undone by knots. We undid the knots and moved on.

The rest our day was a wild success. Through the data we collected we were able to calculate an estimated population size of 3,457. To gauge the accuracy of this estimate we will probably have to head back out to Montaña de Oro and take a complete census of the area.

Circles Are Better Than Lines

As Nathan mentioned, a newer and improved method of measurement was employed on the second day of tree tallying. The transect grid utilized was the same as before, however the transect lines were now used to create intersections on the land. 

Measuring the transects at the border of the plot (road=border)

Each intersection would result in a measuring spot that would be 15m in radius, to create a 148m^2 measuring area. By following a transect line to the intersection of interest (versus trying to walk 5m apart in a straight line down a hill), we were able to more accurately find the measuring point of interest.  

Tape from the road was walked in a relatively straight line to each intersection point. #accuracy

Sometimes life gives you lemons.

Nonetheless, the growth covered landscape still provided enough obstacles to interrupt the seemingly flawless tape-walking-to-measuring-point method. Even so, the new method also provided a much simpler and easier means of counting the trees. Walking in a circle with a fixed15m tape, and counting trees inside of it, proved to be much more consistent than the traveling human transect used in the tree counting 1.0 blog post.


One of the issues Nathan and I ran into dealt with the dispersion of trees in our plot. One of the randomly selected intersections provided us coordinates to an area on the hill that contained substantially less trees than any other spots counted. Oh well.

Leonardo DiCaprio has more Oscars than this plot of land has trees.

-Jeff

Results and Discussion

Results:

With the use of the two different sampling techniques we were able to create two individual population estimates. This helped us to generate a range of possible population sizes. Using the transect method we estimated the eucalyptus population to be 3,229 individuals. The average count in our transects was 43 individuals. The area of the transects were 795m^2 and our total study area was 58,869.42m^2. By dividing the total area by the area of one transect and then multiplying by the average transect count we were able to create a population estimate.

The next sampling method we used was the point count method. Using this we estimated the population size at 3,457. To calculate this we divided the total study area by 706.858m^2 (the area of a single point count) and then multiplied by 41 which was our average count. To our delight these two independent population estimates were in a relatively tight range. This leads us to believe that our estimates were at least precise if not accurate.

Discussion:

The reason that we were interested in the population size of the eucalyptus trees was because it was a unique sampling opportunity. We were curious how difficult it would be to estimate the total number of trees within a forest. On top of that, there are good reasons to be aware of this information for the MDO groves. For example, some people find the eucalyptus trees in MDO to be a pest and an invasive species that prevents the growth of native plants through their allelopathic qualities (Chu et al. 2014). Perhaps these people would be curious of the population size because they would want to know how much it would cost to remove them. Others find the trees to be a crucial part of the state park's look and would want to preserve this grove. Additionally there have been studies that suggest eucalyptus plantations are actually hosts to quite substantial species richness (Timo et al. 2014). They may be interested in if the population size is fluctuating through time. Whatever the case may be, it was an interesting study to tackle and it was a good exercise to sample in such a large study area.

If we were to sample again, using the point count method would probably be our best option. It was not labor intensive and it was easier to be accurate with our counts in this manner. To further refine it, we would use an accurate GPS unit to pinpoint location. We also would find a way to better delineate the outlines of our point counts just to insure that we are 100% accurate in our counts. Regardless, the estimates that we came up with are remarkably close to one another.

Thank you so much for joining us on this adventure. It was a blast and we learned a lot. This is the Eucalyptus Team signing out.

Sources:

Chu, Chaojun, et al. "Allelopathic effects of Eucalyptus on native and introduced tree species." 

     Elsevier: Forest Ecology and Management 323 (2014): 79-84. Print.

Timo, Thiago, Maria Carolina Lyra-Jorge, and Carla Gheler-Costa. "Effect of the plantation age on 
     the use of Eucalyptus stands by medium to large-sized wild mammals in south-eastern Brazil." 
     Biogeosciences and Forestry 8 (2014): 108-33. Print.

Second Day of Data Collection: Seasoned Veterans

View from atop the sand dune looking towards our site.

Early on the third of November, we reembarked to our study site in MDO. Our goal of this outing was to finish collecting sample data using our new point count technique and not lose any members along the way. I arrived at the park well before the rest of the team which allowed my to get another perspective on our study site. Across Pecho Valley Road from our study site are some tremendous sand dunes. Before beginning, I climbed to the top to enjoy a little breakfast by the ocean and get more of a bird's eye view of our study site. There is truly a remarkable number of eucalyptus trees in the park!

Once there we divided into two teams each tasked with collecting several point counts. Jeffrey and I decided to use our old transects to randomly sample from. What we did was generate a number between 1 and 43 that would correspond to a specific transect. Then we selected a number from 1 to 140 that would tell us how many meters to travel down the transect before getting to our sampling area. Once at the randomized location, we used a transect tape to create a large circle with a radius of 15 meters.

Transect tape disappearing into the distance.

This sampling technique did turn out to be less arduous than the transect sampling we tried earlier. There was still a good deal of hiking involved, however, we were not trying to count trees while hiking. This allowed a more focused effort on the sampling task and perhaps gave us more accurate results. Interestingly enough, during a part of the sampling I noticed we were walking on a game trail that was littered in feces. I later learned that they were coyote feces which I though was very exciting to see. This is completely off topic though. So, let's get back to it!

With the combined effort of our two groups were were able to complete 13 point counts which was higher than our goal. It seems that we have developed our forest legs. The results of our second day of data collection are very exciting. There is a remarkable correlation between the estimations generated by our two techniques which makes me confident that we have created a precise range for the eucalyptus population size. I'm not going to give away the punch line here though. For that, stay tuned for our Results and Discussion post, coming soon!

    -Nathan

New Methodology: The Future of the Eucalyptus Team

As we have said in our previous posts, transect sampling turned out to be more difficult to implement than we initially thought. Practically speaking, it required us to walk up and down steep transects and we struggled to keep our lines even as we trudged through poison oak. This sampling method also turned out to be very time consuming. So, we have moved on to plan B: point count sampling.

My footprints looking back down the Bloody Nose Trail

When we go out in the field tomorrow we will be randomly sampling from a selection of many points scattered throughout the study area. We hope that this will give the opportunity to sample a representative grouping of the entire population. Similar to our first field day, we will locate the points using GPS while out in the field. At each point, an imaginary circle with a 15 meter radius will be drawn and every individual eucalyptus tree inside will be counted. If our initial methods testing has any predictive power, than we expect most of our points to contain somewhere around 40 individuals. We hope to sample from at least 10 different points tomorrow. The more we are able to sample from, the more confident we can be in our estimation. Unfortunately, our time constraints may force us to do fewer.

After collecting our data, we will be able to calculate an estimation for the total eucalyptus population within the study area. This is possible because we know the total area of the study site as well as the area of our sampling points. Using the average eucalyptus count from the sampling points,we can calculate the eucalyptus density. From the density we can derive the total population by multiplying the average by the number of times the point area goes into the total area.

But, before we get ahead of ourselves, some field work must be done! Join us next time where we will explore our second sampling excursion and discuss the results of our study.

   -Nathan