Vulnerability of avian populations to renewable energy production

Conkling, Tara J.; Zanden, Hannah B. Vander; Allison, Thomas C.; Diffendorfer, James E.; Dietsch, Thomas V.; Duerr, Adam E.; Fesnock, Amy; Hernandez, Rebecca R.; Loss, Scott R.; Nelson, David M.; Sanzenbacher, Peter M.; Yee, Julie L.; Katzner, Todd E.

doi:10.1098/rsos.211558

Cited by 23 publications

(21 citation statements)

References 71 publications

(91 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Additionally, areas with good wind resources and proximity to end users do not always overlap with existing agricultural area, sometimes requiring wind energy development on previously undeveloped land, as was recently found to be the case in California [ 80 ]. Finally, energy infrastructure can create habitat fragmentation and disturbance that adversely affects wildlife behavior within and beyond the boundary of the physical footprint [ 7 , 37 , 81 – 83 ]. Studies seeking to map existing and future energy infrastructure (e.g., Jenkins et al, 2021) may, in part, inform decisions regarding impacts on wildlife; however, projections including spatially-explicit footprints require robust, accurate, and representative model parameters[ 84 ].…”

Section: Discussionmentioning

confidence: 99%

Land-use intensity of electricity production and tomorrow’s energy landscape

et al. 2022

View full text Add to dashboard Cite

The global energy system has a relatively small land footprint at present, comprising just 0.4% of ice-free land. This pales in comparison to agricultural land use– 30–38% of ice-free land–yet future low-carbon energy systems that shift to more extensive technologies could dramatically alter landscapes around the globe. The challenge is more acute given the projected doubling of global energy consumption by 2050 and widespread electrification of transportation and industry. Yet unlike greenhouse gas emissions, land use intensity of energy has been rarely studied in a rigorous way. Here we calculate land-use intensity of energy (LUIE) for real-world sites across all major sources of electricity, integrating data from published literature, databases, and original data collection. We find a range of LUIE that span four orders of magnitude, from nuclear with 7.1 ha/TWh/y to dedicated biomass at 58,000 ha/TWh/y. By applying these LUIE results to the future electricity portfolios of ten energy scenarios, we conclude that land use could become a significant constraint on deep decarbonization of the power system, yet low-carbon, land-efficient options are available.

show abstract

Section: Discussionmentioning

confidence: 99%

Land-use intensity of electricity production and tomorrow’s energy landscape

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Another advantage of incidental detection is that O&M staff are on site for the life of the facility, potentially offering long-term information on eagle and other large raptor mortality at all operating wind facilities. An improved understanding of eagle mortality would assist wildlife agencies and researchers aiming to evaluate how installed and future wind energy build-out could affect population trends of raptors [37][38][39].…”

Section: Discussionmentioning

confidence: 99%

Incidental eagle carcass detection can contribute to fatality estimation at operating wind facilities

Hallingstad

Riser-Espinoza

Brown

2022

Preprint

View full text Add to dashboard Cite

Risk of birds colliding with wind turbines, especially protected species like bald eagle and golden eagle, is a fundamental wildlife challenge the wind industry faces when developing and operating projects. The U.S. Fish and Wildlife Service requires wind facilities that obtain eagle take permits to document permit compliance through eagle fatality monitoring. If trained Operations and Maintenance (O&M) staff can reliably detect and report carcasses during their normal routines, then their ‘incidental detections’ could contribute substantially to meeting monitoring requirements required by eagle take permits. The primary objective of this study was to quantify incidental detection of eagle carcasses by O&M staff under a variety of landscape contexts and environmental conditions throughout 1 year. We used the incidental detection probabilities (proportion of decoys detected by O&M staff), along with raptor carcass persistence data and area adjustments, to calculate overall probability of incidental detection (i.e., incidental g). We used feathered turkey decoys as eagle-carcass surrogates for monthly detection trials at 6 study sites throughout the U.S. We evaluated the primary drivers of incidental detection using logit regression models including season, viewshed complexity, and a derived variable called the “density quartile” as covariates. We used an Evidence of Absence-based approach to estimate the overall probability of incidental detection. Detection probabilities decreased as viewshed complexity increased and as distance from the turbine increased. The resulting overall probability of incidental detection for the 12-month period ranged from 0.07 to 0.47 (mean = 0.31). The primary drivers of variability in incidental g were detection probability and the area adjustment. Results of our research show that O&M staff were capable of incidentally detecting trial carcasses while performing their typical duties. Incorporating incidental detection by O&M staff in eagle fatality monitoring efforts is a reliable means of improving estimates of a facility’s direct impacts on eagles.

show abstract

“…Accurate eagle and raptor fatality estimates would be advantageous to wildlife agencies and researchers aiming to understand population size, population trends, and population level impacts of mortality. Recent studies have focused on how installed wind energy, and future build-out, could affect population trends of raptors [42][43][44]. However, an acknowledged deficiency of the modeling approaches used in these assessments is that bias correction data for raptors is often aggregated with other large birds (e.g., game birds), making raptor-specific fatality estimates of limited value.…”

Section: The Importance Of Accurate Persistence Estimates In Eagle Fa...mentioning

confidence: 99%

Game Bird Carcasses are Less Persistent Than Raptor Carcasses, But Can Predict Raptor Persistence Dynamics

Hallingstad

Riser-Espinoza

Brown

et al. 2022

Preprint

View full text Add to dashboard Cite

Researchers conduct post-construction fatality monitoring (PCFM) to determine the direct impacts on wildlife caused by operation of a wind energy facility. Results of PCFM can be used to evaluate compliance with permitted take, potentially triggering adaptive management measures or offsetting mitigation; reducing uncertainty in fatality rates benefits wind companies, wildlife agencies, and other stakeholders. As part of PCFM, investigators conduct carcass persistence trials to account for imperfect detection during carcass surveys. In most PCFM studies, pen-raised game birds and other non-raptor surrogates have been used to estimate persistence of all large birds, including raptors. However, there is a growing body of evidence showing carcass persistence varies by bird type; raptor fatality estimates based on game bird carcass persistence may therefore be biased high. We conducted raptor and game bird carcass persistence field trials for 1 year at 6 wind energy facilities. Raptor carcass persistence varied by habitat and season, whereas the best-supported game bird model only included habitat. Raptor persistence probabilities were higher than corresponding game bird persistence probabilities for 13 of the 16 habitat and season combinations. Analysis of a meta-dataset showed that raptor carcass persistence varied by season, habitat, and region. The probability of persisting through a 30-day search interval ranged from 0.44 to 0.99 for raptors and from 0.16 to 0.79 for game birds. Raptor persistence was significantly higher than game bird persistence for 95% of the sampled strata. We used these carcass persistence estimates to develop linear mixed-effects models that predict raptor persistence probabilities based on estimated game bird persistence probabilities. Our scaling model provides an important statistical method to address gaps in raptor persistence data at sites in a broad range of landscape contexts in the continental United States and should be used to inform fatality estimation when site-specific raptor persistence data are limited or absent.

show abstract

Vulnerability of avian populations to renewable energy production

Cited by 23 publications

References 71 publications

Land-use intensity of electricity production and tomorrow’s energy landscape

Land-use intensity of electricity production and tomorrow’s energy landscape

Incidental eagle carcass detection can contribute to fatality estimation at operating wind facilities

Game Bird Carcasses are Less Persistent Than Raptor Carcasses, But Can Predict Raptor Persistence Dynamics

Contact Info

Product

Resources

About