Lesser snow goose ( Anser caerulescens caerulescens ) populations have dramatically altered vegetation communities through increased foraging pressure. In remote regions, regular habitat assessments are logistically challenging and time consuming. Drones are increasingly being used by ecologists to conduct habitat assessments, but reliance on georeferenced data as ground truth may not always be feasible. We estimated goose habitat degradation using photointerpretation of drone imagery and compared estimates to those made with ground-based linear transects. In July 2016, we surveyed five study plots in La Pérouse Bay, Manitoba, to evaluate the effectiveness of a fixed-wing drone with simple Red Green Blue (RGB) imagery for evaluating habitat degradation by snow geese. Ground-based land cover data was collected and grouped into barren, shrub, or non-shrub categories. We compared estimates between ground-based transects and those made from unsupervised classification of drone imagery collected at altitudes of 75, 100, and 120 m above ground level (ground sampling distances of 2.4, 3.2, and 3.8 cm respectively). We found large time savings during the data collection step of drone surveys, but these savings were ultimately lost during imagery processing. Based on photointerpretation, overall accuracy of drone imagery was generally high (88.8% to 92.0%) and Kappa coefficients were similar to previously published habitat assessments from drone imagery. Mixed model estimates indicated 75m drone imagery overestimated barren (F 2,182 = 100.03, P < 0.0001) and shrub classes (F 2,182 = 160.16, P < 0.0001) compared to ground estimates. Inconspicuous graminoid and forb species (non-shrubs) were difficult to detect from drone imagery and were underestimated compared to ground-based transects (F 2,182 = 843.77, P < 0.0001). Our findings corroborate previous findings, and that simple RGB imagery is useful for evaluating broad scale goose damage, and may play an important role in measuring habitat destruction by geese and other agents of environmental change.
The Mike Horse Mine tailings dam in western Montana was partially breached in 1975 due to heavy rainfall and a failed drainage bypass. Approximately 90,000 tons of metal and arsenic-enriched tailings flowed into Beartrap Creek and the Blackfoot River. The spatial distribution of trace elements As, Cd, Cu, Mn, Pb, and Zn in floodplain alluvium of the upper Blackfoot River were examined along 20 transects in the upper 105 river kilometers downstream from the tailings dam. Trace element concentrations decrease with distance from the failed dam, with As reaching background concentrations 15 km from the Mike Horse dam, Cd and Pb at 21 km, Cu at 31 km, and Mn and Zn at 37 km. Distance from the Mike Horse tailings dam and mine area is the dominating factor in explaining trace element levels, with R 2 values ranging from 0.67 to 0.89. Maximum floodplain trace element concentrations in the upper basin exceed US. EPA ecological screening levels for plants, birds and other mammals, and reflect adverse hazard quotients for exposure to As and Mn for ATV/motorcycle use. Trace element concentrations in channel bank and bed alluvium are similar to concentrations in floodplain alluvium, indicating active transport of trace elements through the river and deposition on the floodplain. The fine fraction (\2 mm) of floodplain alluvium is dominated by sand-sized particles (2.0-0.05 mm), with Cu and Mn significantly correlated with silt-sized (0.05-0.002 mm) alluvium. Ongoing remediation in the headwaters area will not address metal contamination stored downstream in the channel banks and on the floodplain. Additionally, some trace elements (Cu, Mn and Zn) were conveyed farther downstream than were others (As, Cd, Pb).
, we estimate that Continental Glacier will be reduced in volume by 43% over the next 100 years and will disappear completely over the next 300-400 years, if current climatic conditions persist.
Runoff from concentrated animal feeding operations and croplands in the Upper Devils Lake Basin (Towner and Ramsey Counties), North Dakota, has the potential to impact the water quality and wildlife of the Lake Alice National Wildlife Refuge. Water samples were collected at eight locations upstream and downstream of the refuge, beginning in June 2007 through March 2011, to identify the spatial distribution of water quality parameters and assess the potential impacts from the upstream land use practices. Geographic Information Systems, statistical analysis, and regulatory standards were used to differentiate between sample locations, and identify potential impacts to water quality for the refuge based on 20 chemical constituents. Kruskal-Wallis analysis of variance (ANOVA) showed significant differences between sample locations based on boron, calcium, Escherichia coli, phosphorus, aluminum, manganese, and nickel. Hierarchical agglomerative cluster analysis of these constituents identified four distinct water quality groupings in the study area. Furthermore, this study found a significant positive correlation between the nutrient measures of nitrate-nitrite and total Kjeldahl nitrogen, and the percentage of concentrated animal feeding operation nutrient management areas using the non-parametric Spearman rho method. Significant correlations were also noted between total organic carbon and nearness to concentrated animal feeding operations. Finally, dissolved oxygen, pH, sulfate, E. coli, total phosphorus, nitrate-nitrite, and aluminum exceeded state of North Dakota and/or US Environmental Protection Agency water quality standards and/or guidelines. Elevated concentrations of phosphorus, nitrate-nitrite, and E. coli from upstream sources likely have the greatest potential impact on the Lake Alice Refuge.
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