Site-Occupancy Monitoring Of An Ecosystem Indicator: Linking Characteristics Of Riparian Vegetation To Beaver Occurrence

Establishment of sampling frameworks to monitor the occurrence of ecological indicators and to identify the covariates that influence occurrence is a high-priority need for natural resource restoration and management efforts. We utilized occupancy modeling to identify patterns of beaver occurrence and factors influencing these patterns (i.e., type and amount of vegetation cover) in the Grand Canyon of the Colorado River ecosystem. We used rafts and kayaks to access a stratified random sample of sites (i.e., 100-m-long sections of riverbank) and used repeated sampling procedures to sample for beaver sign (i.e., lodges, cuttings, tracks, and beaver sightings). We quantified the type and amount of vegetation cover at each sampled section by using a GIS database of remotely sensed information on the riparian vegetation in the Grand Canyon. We first modeled occurrence of beaver sign as a function of the total amount of vegetation cover (summed across classes) and then determined the relative importance score for each of the 7 vegetation classes. Detection probability (p) was 2 times higher when observers traveled in kayaks (0.61) than when they traveled in rafts (0.29). Occurrence of beaver sign (ψ) in sampled transects was widespread throughout the Grand Canyon (ψ = 0.74, SE = 0.06) and positively associated with total vegetation. The relative importance scores for Tamarix and Pluchea vegetation classes were 1.5–2.5 times larger than those for all other vegetation classes, indicating that occurrence of beaver sign was most strongly associated with the cover of these 2 vegetation classes. Our results imply that quantifying the amount of riparian vegetation in close proximity to a river helps determine the occurrence of an important ecological indicator in riparian systems. The results also demonstrate a useful and cost-effective method for monitoring riverine species’ usage patterns by explicitly accounting for detectability

Interrelationships among northern flying squirrels, truffles, and microhabitat structure in Sierra Nevada old-growth habitat

During 1997–1998, we investigated the influence of both the relative abundance of truffles, preferred food items, and microhabitat structure on the occurrence of northern flying squirrels (Glaucomys sabrinus Shaw) in old-growth forest habitat of the Sierra Nevada Range, U.S.A. Following live-trapping sessions, we searched the forest floor for truffle diggings and sampled the soil for truffles. Diggings were more abundant where flying squirrels were captured, suggesting squirrels were active near areas of the forest floor where truffles had recently been excavated. The frequency of sampling plots with truffles was higher where squirrels were captured, further suggesting preferences for microhabitats where truffles were more abundant. We also measured 15 microhabitat variables at trap stations to evaluate the influence of aboveground microhabitat characteristics on squirrel occurrence. Results indicated that flying squirrels preferred microhabitats with understory cover, which may minimize predation from aerial predators like spotted owls (Strix occidentalis Merriam). Neither abundance of coarse woody debris, a feature conducive to fungal growth, nor the abundance of potential nesting sites (i.e., snags) measurably influenced squirrel occurrence. While various aboveground forest-microhabitat characteristics affect the use of old-growth forests by flying squirrels, these animals refine their use of these forests based on fine-scale changes in the availability of a highly preferred and ephemeral food item

Interrelationships among northern flying squirrels, truffles, and microhabitat structure in Sierra Nevada old-growth habitat

During 1997–1998, we investigated the influence of both the relative abundance of truffles, preferred food items, and microhabitat structure on the occurrence of northern flying squirrels (Glaucomys sabrinus Shaw) in oldgrowth forest habitat of the Sierra Nevada Range, U.S.A. Following live-trapping sessions, we searched the forest floor for truffle diggings and sampled the soil for truffles. Diggings were more abundant where flying squirrels were captured, suggesting squirrels were active near areas of the forest floor where truffles had recently been excavated. The frequency of sampling plots with truffles was higher where squirrels were captured, further suggesting preferences for microhabitats where truffles were more abundant. We also measured 15 microhabitat variables at trap stations to evaluate the influence of aboveground microhabitat characteristics on squirrel occurrence. Results indicated that flying squirrels preferred microhabitats with understory cover, which may minimize predation from aerial predators like spotted owls (Strix occidentalis Merriam). Neither abundance of coarse woody debris, a feature conducive to fungal growth, nor the abundance of potential nesting sites (i.e., snags) measurably influenced squirrel occurrence. While various aboveground forest-microhabitat characteristics affect the use of old-growth forests by flying squirrels, these animals refine their use of these forests based on fine-scale changes in the availability of a highly preferred and ephemeral food item

Evaluating the accuracy of unmanned aerial systems to quantify glacial ice habitats of harbor seals in Alaska

Abstract Long‐term monitoring programs to evaluate climate‐driven changes to tidewater glaciers, an important habitat for harbor seals (Phoca vitulina) in Alaska, are primarily carried out by costly, weather‐dependent aerial surveys from fixed‐winged aircraft. Unmanned aerial systems (UAS) can be an alternative cost‐effective solution for gathering image data to quantify, monitor, and manage these habitats. However, there is a paucity of information related to the accuracy of using imagery collected by UAS for purposes of measuring floating icebergs. We evaluated the accuracy of using a UAS with a built‐in 20‐megapixel (MP) camera as well as a consumer‐grade digital 16‐MP camera to capture images of floating and stationary icebergs for the purpose of collecting vertical height measurements. Images (n = 869) were captured of simulated icebergs (cuboidal foam boxes, Cb) (n = 5) and real icebergs (n = 5) that were either grounded or floating. The mean error ratios (Ers) obtained were less than 10% and derived by comparing the mean calculated measurements of heights of Cb obtained from images captured by UAS with the physically measured heights of these Cb. The mean Er for height measurements of grounded icebergs (n = 4) and one floating iceberg was also less than 10%. Within an object–image distance range of 6–25 m, the cameras captured images that were suitable to accurately calculate the heights of floating and grounded objects, and drift or uncontrolled movement of the UAS caused by wind or temporary loss of GPS did not have any effect on measurement error. Our study provides substantial evidence of the accuracy associated with using images captured by UAS for measuring dimensions of structures positioned on either water or land surfaces. Ultimately, accurate surveys of glacial ice used by harbor seals will improve our understanding of the role of decreasing habitat in explaining population variability between different tidewater glaciers

Evaluating the Accuracy of Unmanned Aerial Systems to Quantify Glacial Ice Habitats of Harbor Seals in Alaska

Long-term monitoring programs to evaluate climate-driven changes to tidewater glaciers, an important habitat for harbor seals (Phoca vitulina) in Alaska, are primarily carried out by costly, weather-dependent aerial surveys from fixed-winged aircraft. Unmanned aerial systems (UAS) can be an alternative cost-effective solution for gathering image data to quantify, monitor, and manage these habitats. However, there is a paucity of information related to the accuracy of using imagery collected by UAS for purposes of measuring floating icebergs. We evaluated the accuracy of using a UAS with a built-in 20 megapixel (MP) camera as well as a consumer-grade digital 16 MP camera to capture images of floating and stationary icebergs for the purpose of collecting vertical height measurements. Images (n=869) were captured of simulated icebergs (Cuboidal foam boxes) “Cb” (n=5) and real icebergs (n=5) that were either grounded or floating. The mean error ratios obtained were less than 10% and derived by comparing the mean calculated measurements of heights of Cb obtained from images captured by UAS with the physical measured heights of these Cb. The mean error ratio for height measurements of grounded icebergs (n=4) and one floating iceberg was also less than 10%. Within an object-image distance range of 6-25 m, the cameras captured images that were suitable to accurately calculate the heights of floating and grounded objects, and drift or uncontrolled movement of the UAS caused by wind or temporary loss of GPS did not appear to have any significant effects on measurement error. Our study provides substantial evidence of the high accuracy associated with using images captured by UAS for measuring dimensions of structures positioned on water and land surfaces. Ultimately, accurate surveys of glacial ice used by harbor seals will improve our understanding about the role of decreasing habitat in explaining population variability between different tidewater glaciers.Funding was provided by the Resilience and Adaptation Program at the University of Alaska Fairbanks, the Rasmuson Foundation, the Carlson scholarship, Alaska EPSCoR NSF award #OIA-1757348 and the State of Alaska, the Biomedical Learning and Student Training (BLaST) Program through the National Institute of General Medical Sciences of the National Institutes of Health under three linked awards number RL5GM118990, TL4GM118992 and 1UL1GM118991, and The Alaska Center for Climate Assessment & Policy (ACCAP). National Marine Fisheries Service (NMFS) John Jansen and Steve Lewis, Kaja BrixYe

Data from: Effects of the landscape on boreal toad gene flow: does the pattern-process relationship hold true across distinct landscapes at the northern range margin?

Understanding the impact of natural and anthropogenic landscape features on population connectivity is a major goal in evolutionary ecology and conservation. Discovery of dispersal barriers is important for predicting population responses to landscape and environmental changes, particularly for populations at geographic range margins. We used a landscape genetics approach to quantify the effects of landscape features on gene flow and connectivity of boreal toad (Bufo boreas) populations from two distinct landscapes in Southeast Alaska (Admiralty Island, ANM, and the Chilkat River Valley, CRV). We used two common methodologies for calculating resistance distances in landscape genetics studies (resistance based on least-cost paths and circuit theory). We found a strong effect of saltwater on genetic distance of CRV populations, but no landscape effects were found for the ANM populations. Our discordant results show the importance of examining multiple landscapes that differ in the variability of their features, in order to maximize detectability of underlying processes and allow results to be broadly applicable across regions. Saltwater serves as a physiological barrier to boreal toad gene flow and affects populations on a small geographic scale, yet there appear to be few other barriers to toad dispersal in this intact northern region

Regression models describing the relationship between mean daily stream temperature and mean daily DO in A) Peterson Creek and B) Cowee Creek during the 1 May through 31 October, 2013 study period.

<p>Regression models describing the relationship between mean daily stream temperature and mean daily DO in A) Peterson Creek and B) Cowee Creek during the 1 May through 31 October, 2013 study period.</p

Regression models describing the relationship between mean daily stream temperature and mean daily DO in A) Peterson Creek and B) Cowee Creek during the 1 May through 31 October, 2013 study period.

<p>Regression models describing the relationship between mean daily stream temperature and mean daily DO in A) Peterson Creek and B) Cowee Creek during the 1 May through 31 October, 2013 study period.</p