GEOG 566

         Advanced spatial statistics and GIScience

April 6, 2018

What landscape factors are most important to predicting beaver dam occurrence in the Oregon Coast Range?

Filed under: 2018,My Spatial Problem @ 5:51 pm

Project Overview:

North American beavers (Castor canadensis) are often referred to as ‘ecosystem engineers’ because they can fundamentally transform stream and riparian ecosystems through dam building, pond creation, and intensive foraging on vegetation. Recent literature suggests that beaver restoration via, introduction of beavers to unoccupied stream reaches, may provide for a cost-effective strategy to restore degraded watersheds. Despite these potential benefits there is also considerable uncertainty around the efficacy of beaver restoration including 1) survival of reintroduced beavers, 2) what constitutes suitable habitat for dam building, 3) quantifiable benefits of those dams, and 4) possible mal-effects or unintended consequences of beaver restoration efforts, such as flooding and damage to private property.   The goal of this analysis to consider what landscape factors can be used to predict 1) the presence or absence of beaver occupancy and 2) presence or absence of beaver dams in the West Fork Cow Creek, a tributary of the South Umpqua River in Southern Oregon.


These questions will be analyzed using data that were collected during beaver occupancy and dam presence surveys in the West Fork of Cow Creek (WFCC) during August and September of 2017. A total of 144 survey locations were sampled from the basin using metrics of stream gradient, bank-full stream width, and valley floor width. Using these geomorphic characteristics, survey locations were organized into three strata: 1) suitable for damming habitat and beaver occupancy; 2) unsuitable damming habitat but suitable for beaver occupancy, and 3) unsuitable for damming habitat and beaver occupancy. Surveys were collected along longitudinal transects upstream from the survey locations to 100m upstream.


  1. Availability of suitable beaver dam habitat will be most limited by stream gradients in the West Fork Cow Creek.

Literature on suitable damming habitat identifies more than a dozen variables that have been used to predict dam sites in watersheds throughout North America (Dittbrenner et al., 2018) but generally include factors related to perennial streamflow, stream geomorphology and food supply. In the Oregon Coast Range, dams sites have been found to occur most commonly in stream reaches with low gradient (≤ 5%), moderate bank-full width (3-6m) and wide valley floors (≥25m) (Suzuki & McComb, 1998). These characteristics reflect the criteria for selection of stream reaches in Stratum 1. However, it is not clear that each of these factors exert an equal influence on the occurrence of beaver dams with evidence that stream slope may be the most important factor because of high annual precipitation and the generally steep, dissected nature of the regions watersheds that produce high seasonal peak flows that can cause dam failures.

  1. Observed dams sites will occur more frequency where connectivity among suitable damming habitat is greatest.

Connectivity and neighborhood effects are important factors in habitat selection studies. For example, Issak et al. (2007) found Chinook salmon preferentially selected spawning locations with greater habitat size and connectivity over habitat quality. (Isaak Daniel J., Thurow Russell F., Rieman Bruce E., & Dunham Jason B., 2007). To my understanding these factors have not been well considered in efforts to predict the occurrence of beaver dam sites across watersheds.


I would like to build a logistic regression model that considers the occurrence of beaver dams sites based on a number of explanatory variables including, stream slope, bankfull width, valley slope, connectivity, and proximity to non-damming beavers.

Expected Outcome:

My goal in this effort to develop a predictive model of where beaver dams are either most likely to occur, or identify‘opportunity areas’, i.e. where dam sites could occur with beaver introductions in the West Fork Cow Creek drainage. This would include maps of predicted dam locations, and dammed stream reaches as well as locations where conflict may arise due to proximity to roads or agricultural lands.


There have been growing interest in the Umpqua River Basin among stakeholders and watershed managers to explore what opportunities beaver restoration may provide to watershed enhancement. A predictive tool would provide guidance and help to improve chances of success in relocation of beavers.

Level of preparation:

My experience with Arc-Info is low to moderate and it has been quite some time since I used any of the ESRI products on a regular basis so I anticipate there will be a challenging learning curve. Over the past 6 months I have been using R studio and feel moderately comfortable running regression analyses and developing basic charts and figures. I have no experience with Python.


Dittbrenner, B. J., Pollock, M. M., Schilling, J. W., Olden, J. D., Lawler, J. J., & Torgersen, C. E. (2018). Modeling intrinsic potential for beaver (Castor canadensis) habitat to inform restoration and climate change adaptation. PLOS ONE, 13(2), e0192538.

Isaak Daniel J., Thurow Russell F., Rieman Bruce E., & Dunham Jason B. (2007). Chinook salmon use of spawning patches: relative roles of habitat quality, size, and connectivity. Ecological Applications, 17(2), 352–364.

Suzuki N, McComb WC. Habitat classification models for beaver (Castor canadensis) in the streams of the central Oregon Coast Range. Northwest Sci. 1998;72: 102–110.


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1 Comment

  1.   jonesju — April 9, 2018 @ 8:37 am    

    hi John,
    Thanks for your blog post. It appears that the variable of interest (dependent variable) is survey locations – is that correct? (Do you have data on actual beaver dam locations? Can you clarify this in your post please?). Therefore I suggest that you start by creating a GIS layer showing the locations of the surveyed sites, and that you attribute each site with the relevant data which you measured. At each site, do you have multiple observations of a single variable along a 100-m transect? Do you need to create GIS layers showing the spatial patterns within each transect? Or will each site be characterized (attributed) based on average or summary values? I suggest that you try to describe the GIS layer that you could create, and then try to create it.

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