Resource Documents: Oregon (10 items)
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Evidence of region-wide bat population decline from long-term monitoring and bayesian occupancy models with empirically informed priors
Author: Rodhouse, Thomas; et al.
Strategic conservation efforts for cryptic species, especially bats, are hindered by limited understanding of distribution and population trends. Integrating long‐term encounter surveys with multi‐season occupancy models provides a solution whereby inferences about changing occupancy probabilities and latent changes in abundance can be supported. When harnessed to a bayesian inferential paradigm, this modeling framework offers flexibility for conservation programs that need to update prior model‐based understanding about at‐risk species with new data. This scenario is exemplified by a bat monitoring program in the Pacific Northwestern United States in which results from 8 years of surveys from 2003 to 2010 require updating with new data from 2016 to 2018. The new data were collected after the arrival of bat white‐nose syndrome and expansion of wind power generation, stressors expected to cause population declines in at least two vulnerable species, little brown bat (Myotis lucifugus) and the hoary bat (Lasiurus cinereus). We used multi‐season occupancy models with empirically informed prior distributions drawn from previous occupancy results (2003–2010) to assess evidence of contemporary decline in these two species. Empirically informed priors provided the bridge across the two monitoring periods and increased precision of parameter posterior distributions, but did not alter inferences relative to use of vague priors. We found evidence of region‐wide summertime decline for the hoary bat (λ trend = 0.86 ± 0.10) since 2010, but no evidence of decline for the little brown bat (λ trend = 1.1 ± 0.10). White‐nose syndrome was documented in the region in 2016 and may not yet have caused regional impact to the little brown bat. However, our discovery of hoary bat decline is consistent with the hypothesis that the longer duration and greater geographic extent of the wind energy stressor (collision and barotrauma) have impacted the species. These hypotheses can be evaluated and updated over time within our framework of pre–post impact monitoring and modeling. Our approach provides the foundation for a strategic evidence‐based conservation system and contributes to a growing preponderance of evidence from multiple lines of inquiry that bat species are declining.
Thomas J. Rodhouse, National Park Service and Human and Ecosystem Resiliency and Sustainability Lab, Oregon State University—Cascades, Bend
Rogelio M. Rodriguez, Human and Ecosystem Resiliency and Sustainability Lab, Oregon State University—Cascades, Bend
Katharine M. Banner, Department of Mathematical Sciences, Montana State University, Bozeman
Patricia C. Ormsbee, Willamette National Forest, Springfield, Oregon
Jenny Barnett, Mid‐Columbia River National Wildlife Refuge Complex, U.S. Fish and Wildlife Service, Burbank, Washington
Kathryn M. Irvine, Northern Rocky Mountain Science Center, U.S. Geological Survey, Bozeman, Montana
Ecology and Evolution. 2019;00:1–11.
First published: 11 September 2019
Author: Smallwood, Shawn
On behalf of Friends of the Columbia Gorge, Oregon Wild, the Oregon Natural Desert Association, Central Oregon LandWatch, the Audubon Society of Portland, and East Cascades Audubon Society, I write to comment on the Request for Amendment 4 for the Summit Ridge Wind Farm, which requests a postponement of construction start and end dates for the project and which proposes an amended Habitat Mitigation Plan (January 2019). I primarily wish to comment on (1) the suitability of the habitat assessment underlying the amended Habitat Mitigation Plan, and (2) the need to update baseline surveys, project impact predictions, mitigation measures, and post-construction monitoring protocols. Updated surveys and analyses are needed in part because over the near-decade that has passed since the primary baseline study (Northwest Wildlife Consultants 2010), science has made vast improvements in field survey methods and in our understanding of wind turbine collision factors, displacement effects, and cumulative impacts related to wind projects. Methodology has vastly improved in preconstruction studies needed to predict project-scale and wind turbine-scale impacts, to measure post-construction impacts, and to assess whether and to what degree specific mitigation measures can be tested for efficacy. …
Skilled Dog Detections of Bat and Small Bird Carcasses in Wind Turbine Fatality Monitoring. K. Shawn Smallwood, Doug Bell, Skye Standish. 16 February 2018
Comparison of Wind Turbine Collision Hazard Model Performance Prepared for Repowering Projects in the Altamont Pass Wind Resources Area. K. Shawn Smallwood and Lee Neher. 7 January 2017 (Updated 5 April 2018)
Addendum to Comparison of Wind Turbine Collision Hazard Model Performance: One-year Post-construction Assessment of Golden Eagle Fatalities at Golden Hills. K. Shawn Smallwood. 10 April 2018
Download original document: “Smallwood – Re: Summit Ridge Wind Farm – Request for Amendment 4”
Author: Kolar, Patrick; and Bechard, Marc
ABSTRACT: Quantifying the rate of turbine collision mortality for raptors has been the primary focus of research at wind energy projects in Europe and the United States. Breeding adults and fledglings may be especially prone to collisions, but few studies have assessed the consequences of increased mortality and indirect effects from this type of development activity on reproduction. We examined the influence of wind turbines and other factors on nest success and survival of radio-marked juveniles during the post-fledging period for 3 sympatric breeding Buteo species in the Columbia Plateau Ecoregion (CPE), Oregon, USA. Nest success for ferruginous hawks (Buteo regalis) decreased as the number of wind turbines within the home range buffer (32 km²) increased. There was no effect of turbines on nest success for red-tailed hawks (Buteo jamaicensis) or Swainson’s hawks (Buteo swainsoni). Of 60 nestlings radio-marked from all 3 species, we found no evidence that any were killed as a result of collisions with wind turbines after fledging. This was likely due, in part, to the limited size of the natal home range and the relatively short duration of the post-fledging period. However, juveniles of all 3 species hatched from nests in areas of greater turbine density were more likely to die from predation or starvation just after fledging and prior to becoming independent compared to those in areas of lower turbine density. Taken together, these results suggest that wind turbines affected reproductive efforts by all 3 species to some degree, but these effects were greater for ferruginous hawks compared to the other 2 congeneric species. The causes of this negative association are unknown but likely represent some combination of breeding adults being killed from turbine collisions, disturbed from activities associated with the increasing wind energy development in the area, or displaced from portions of their home range to minimize the risk of disturbance or death. The potential for these effects necessitate that planning of future wind energy facilities be considered at larger geographic scales beyond the placement of individual turbines to limit development near raptor breeding areas.
PATRICK S. KOLAR and MARC J. BECHARD
Raptor Research Center, Department of Biological Science, Boise State University, Boise, ID
The Journal of Wildlife Management; DOI: 10.1002/jwmg.21125
Volume 80, Issue 7, September 2016, Pages 1242–1255
Download original document: “Wind Energy, Nest Success, and Post-Fledging Survival of Buteo Hawks”
Home Range and Resource Selection by GPS-Monitored Adult Golden Eagles in the Columbia Plateau Ecoregion: Implications for Wind Power Development
Author: Watson, James; Duff, Andrew; and Davies, Robert
ABSTRACT: Recent national interest in golden eagle (Aquila chrysaetos) conservation and wind energy development prompted us to investigate golden eagle home range and resource use in the Columbia Plateau Ecoregion (CPE) in Washington and Oregon. From 2004 to 2013, we deployed satellite transmitters on adult eagles (n = 17) and monitored their movements for up to 7 years. We used the Brownian bridge movement model (BBMM) to estimate range characteristics from global position system (GPS) fixes and flight paths of 10 eagles, and modeled resource selection probability functions (RSPFs). Multi-year home ranges of resident eagles were large (99% volume contour; x̄ = 245:7 km², SD = 370.2 km²) but were onethird the size (x̄ = 82:3 km², SD = 94.6 km²) and contained half as many contours when defined by 95% isopleths. Annual ranges accounted for 66% of multi-year range size. During the breeding season (16 Jan–15 Aug), eagles occupied ranges that were less fragmented, about half as large, and largely contained within ranges they used outside the breeding season (x̄ overlap = 82.5%, SD = 19.0). Eagles selected upper slopes, rugged terrain, and ridge tops that appear to reflect underlying influences of prey, deflective wind currents, and proximity to nests. Fix distribution predicted by our resource selection model and that of 4 eagles monitored independently in the CPE were highly correlated (rs = 0.992). Our findings suggest conservative landscape management strategies addressing development in lower-elevation montane and shrub-steppe/ grassland ecosystems can best define golden eagle ranges using exclusive 12.8-km buffers around nests. Less conservative strategies based on 9.6-km buffers must include identification and management of upper slopes, ridge-tops, and areas of varied terrain defined by predictive models or GPS telemetry. For both strategies, high, year-round intensity of eagle flight and perch use within 50% volume contours (average 3.2 km from nests) due to nest centricity may dramatically increase the probability of eagle conflict with wind turbines in core areas as evidenced by eagle turbine strikes that studies have documented within and beyond this zone.
JAMES W. WATSON, ANDREW A. DUFF, and ROBERT W. DAVIES
Washington Department of Fish and Wildlife, Olympia, WA, USA
The Journal of Wildlife Management 78(6):1012–1021; 2014; DOI: 10.1002/jwmg.745