This entry details a portion of my thesis work at the University of Alaska Fairbanks, and is intended to communicate the findings of that work in a four part series. You are reading part four examining the likelihood of competition between wolves and humans. In order to make the article concise, you may review the general background of this work in part one. I have truncated the background and methods of this work and focused on a portion of the results.
In parts two and three of this series I have been examining where humans in the Yukon Flats, Alaska are traveling to harvest moose and where/how wolves are traveling to harvest moose. A key finding of human access was that humans are mostly operating within 1500 meters of navigable water. During our wolf study I found that travel was based around river corridors. Based on this, I will conclude this series of articles by examining the “Beaver Creek” pack which overlapped strongly with navigable water.
I wanted to begin to understand the likelihood of competition around navigable waters for moose between humans and wolves. Remember, moose exist at extremely low densities and humans and wolves depend on them as a food resource. Therefore, I believe understanding competition is particularly important. To understand the likelihood of competition, I applied my model of human access and overlapped it with wolf locations. I found that 75% of wolf use locations fell within the human access model.
This figure demonstrates the overlap in points between the human access model that I created (part two), and the wolf points (part 3). Beaver Creek pack falls on navigable water, and hence the likelihood of competition is greatest there.
My analysis does not contain temporally overlapping data. Wolf habitat selection may differ in September and October when humans are hunting moose. Wolves could also rely on other prey species other than moose during that period. Also, predation in the Yukon Flats extends beyond wolves. Bears take up to 85% of moose calves each spring. As such, my conclusion is just the beginning research for future biologists in the region. A complete analysis would encompass all predation on moose, be spatially and temporally overlapping, and would evaluate how many moose which are predated could be taken by humans. I hope you have enjoyed this four part series! A full copy of the thesis can be obtained by contacting me. Feel free to do so!
This entry details a portion of my thesis work at the University of Alaska Fairbanks, and is intended to communicate the findings of that work in a four part series. You are reading part two. In order to make the article concise, you may review the general background of this work in part one. I have truncated the background and methods of this work and focused on a portion of the results.
How do you get to a resource? Well, the simple answer is you “access” them. Depending on what you are trying to achieve, access may mean walking through the door of your local grocery store, driving onto a frozen lake and drilling a hole to jig up a fish, or driving a boat up a river to harvest a moose. The last example speaks directly to subsistence use patterns of communities in the Yukon Flats, Alaska. The objective of this part (specifically Chapter 1) of my study was quantify rural hunter access in Alaska.
This is an image for Fort Yukon in the spring. The Yukon River dominates the landscape. Fort Yukon is ~500 people, and the other communities I studied range from 30 – 100 people.
Let’s take a step backward quickly to look at why access matters. Game levels are traditionally managed to create yield for hunters, but it is critical that game populations be accessible to hunters. In the huge area of Alaska, creating high game densities in a remote region may have minimal benefit to hunters. Outside of Alaska, the effect of access on game populations and hunter success is not well understood, but increased access in Ontario may decrease moose, increased access in Idaho may increase elk mortality, and hunters in Minnesota concentrate their efforts within 0.8 km of roads 98% of the time. These studies suggest that access is important, but within the Arctic access has not been quantified despite being important for hunters, particularly those with a subsistence lifestyle.
It is important that game managers understand how many animals are being harvested to aid in setting regulations. In Alaska, this is accomplished by reporting harvest via a “harvest tag”. However, under-reporting of harvest via the harvest tag system is high in the subsistence communities of the Yukon Flats. This is due to a variety reasons centering around culture practices and feasibility of reporting. Within those communities, moose hunters are allowed one bull moose per season, and hunting most often occurs along rivers in September and October.
To understand where moose hunters are harvesting moose, I used an interview dataset collected in 2005 and 2007 by the Council of Athabascan Tribal Governments. The interviews were in conducted in five subsistence communities including Fort Yukon, Beaver Creek, Circle, Arctic Village, and Birch Creek. In the interview process, interviewees recorded harvest locations of moose on a topographic map. Based on that we determined they utilized rivers, a hunting method that is well documented in other research. However, the data allowed me go beyond just determining river use. I wanted to know : how far were users traveling from their community and from the river to harvest moose?
The study area was reviewed in part 1 of this four part series. This figure demonstrates the five communities that I studied, and their relation to each other.
I designed a method to quantify hunter access. I measured the straight-line distance of the harvest points from their community of origin, and the distance from the rivers. The idea behind this is that the hunter moved up river to a certain point, and then moved away from the river a certain distance. I grouped the resulting distances into five groups, and created a buffer around communities and rivers based on those distances. Within the buffers, I developed an “access index” with the goal of understanding the likelihood that a hunter would utilize an area. The access index was calculated as the number of points that fell inside of a buffer divided by the total number of points up to the edge of that buffer. So, based on that the maximum achievable value was 100% and either existed near community, or near the rivers. In effect, 100% means that 100% of the time, hunters were willing to travel that distance to harvest a moose.
This schematic illustrates the calculation of the access index. I buffered rivers and each of the five communities base on the distances to harvest points. Within each of the buffers I calculated an access index, with the buffer around rivers and communities equaling 100%. In the first buffer hunters were 100% likely to travel at least that far to harvest a moose.This final model demonstrates how access if focused around rivers, and around communities. In this image, I added together of the access index around each of the five communities, and around the rivers.
The approach that I took was novel, and yielded some useful results. We found that on average hunters were traveling 0.9 ± 0.6 km from rivers and 47km ± 32km from their communities. Harvest was centered around rivers, and was happening most frequently near rivers. Some useful results!
There are a few ways that this model may be applied. First, I applied a region density of 0.0016 bull moose per square kilometer (remember, there are VERY low moose densities) to estimate the number of legal moose that are available to moose hunters. Based on hunter success of 27 – 46%, I estimated that 98 – 176 moose are harvested by hunters annually. Those numbers fell into the reasonable range of reported harvest in the region. Seeing as that’s the case, this method could help managers understand the amount of moose harvested, instead of relying on the extremely (regionally) variable harvest ticket system. Since this model enables an estimate of the number of animals taken around an access corridor, it could be used in other hunting systems where access is important. For instance in Alaska if a new road was created, how many moose would be harvested based on the new access. In Idaho, how many elk would be preserved if a road is closed?
Overall the results of this study have applicability within my study system, other subsistence systems in Alaska, and more broadly to regions where harvest of game is linked to access. It demonstrates a novel method, and the results that can be gained through an interview process. In the next portion of this series, I will be examining wolf movement in this same area, which yielded some great results.
*The entirety of this work is in review with the Journal of Human Dimensions of Wildlife
