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Manuela M. Huso

Publications and source records attributed to Manuela M. Huso.

16 recordsLinked to original sources
USGS2019

Wildlife mortality at wind facilities: How we know what we know how we might mislead ourselves, and how we set our future course

To accurately estimate per turbine – or per megawatt – annual wildlife mortality at wind facilities, the raw counts of carcasses found must be adjusted for four major sources of imperfect detection: (1) fatalities that occur outside the monitoring period; (2) carcasses that land outside the monitored area; (3) carcasses that are removed by scavengers or deteriorate beyond recognition prior to detection; and (4) carcasses that remain undiscovered by searchers even when present. To accurately estimate regional or national annual wildlife mortality, data must come from a representative (or appropriately weighted) sample of facilities for which estimates of mortality account for all sources of imperfect detection. I argue that the currently available data in the United States and much of the world do not represent the impacts of wind power on wildlife because not all facilities conduct monitoring studies, not all study results are publicly available, and few studies adequately account for imperfect detection. I present examples illustrating the limitations of our current data and pitfalls of interpreting data without accurately adjusting for detection bias. I close by proposing a solution through a simplified monitoring process that can be applied at every facility as part of normal operations. Application of an unbiased estimator that accounts for all sources of imperfect detection would assure comparability of mortality estimates. Public access to reported estimates would achieve representation. With these data we could develop a clearer understanding of how wind power is affecting wildlife throughout the world and inform our efforts to address it.

Book chapter↗
USGS2019

Impacts to wildlife of wind energy siting and operation in the United States

Electricity from wind energy is a major contributor to the strategy to reduce greenhouse gas emissions from fossil fuel use and thus reduce the negative impacts of climate change. Wind energy, like all power sources, can have adverse impacts on wildlife. After nearly 25 years of focused research, these impacts are much better understood, although uncertainty remains. In this report, we summarize positive impacts of replacing fossil fuels with wind energy, while describing what we have learned and what remains uncertain about negative ecological impacts of the construction and operation of land-based and offshore wind energy on wildlife and wildlife habitat in the U.S. Finally, we propose research on ways to minimize these impacts. TO SUMMARIZE: 1 Environmental and other benefits of wind energy include near-zero greenhouse gas emissions, reductions of other common air pollutants, and little or no water use associated with producing electricity from wind energy. Various scenarios for meeting U.S. carbon emission reduction goals indicate that a four- to five-fold expansion of land-based wind energy from the current 97 gigawatts (GW) by the year 2050 is needed to minimize temperature increases and reduce the risk of climate change to people and wildlife. 2 Collision fatalities of birds and bats are the most visible and measurable impacts of wind energy production. Current estimates suggest most bird species, especially songbirds, are at low risk of population-level impacts. Raptors as a group appear more vulnerable to collisions. Population-level impacts on migratory tree bats are a concern, and better information on population sizes is needed to evaluate potential impacts to these species. Although recorded fatalities of cave-dwelling bat species are typically low at most wind energy facilities, additional mortality from collisions is a concern given major declines in these species due to white-nose syndrome (WNS). Assessments of regional and cumulative fatality impacts for birds and bats have been hampered by the lack of data from areas with a high proportion of the nation’s installed wind energy capacity. Efforts to expand data accessibility from all regions are underway, and this greater access to data along with improvements in statistical estimators should lead to improved impact assessments. 3 Habitat impacts of wind energy development are difficult to assess. An individual wind energy facility may encompass thousands of acres, but only a small percentage of the landscape within the project area is directly transformed. If a project is sited in previously undisturbed habitat, there is concern for indirect impacts, such as displacement of sensitive species. Studies to date indicate displacement of some species, but the long-term population impacts are unknown. 4 Offshore wind energy development in the U.S. is just beginning. Studies at offshore wind facilities in Europe indicate some bird and marine mammal species are displaced from project areas, but substantial uncertainty exists regarding the individual or population-level impacts of this displacement. Bird and bat collisions with offshore turbines are thought to be less common than at terrestrial facilities, but currently the tools to measure fatalities at offshore wind energy facilities are not available. The wind energy industry, state and federal agencies, conservation groups, academia, and scientific organizations have collaborated for nearly 25 years to conduct the research needed to improve our understanding of risk to wildlife and to avoid and minimize that risk. Efforts to reduce the uncertainty about wildlife risk must keep up withthe pace and scale of the need to reduce carbon emissions. This will require focusing our research priorities and increasing the rate at which we incorporate research results into the development and validation of best practices for siting and operating wind energy facilities.

Issues in Ecology↗
USGS2018

GenEst statistical models—A generalized estimator of mortality

Introduction GenEst (a generalized estimator of mortality) is a suite of statistical models and software tools for generalized mortality estimation. It was specifically designed for estimating the number of bird and bat fatalities at solar and wind power facilities, but both the software (Dalthorp and others, 2018) and the underlying statistical models are general enough to be useful in various situations to estimate the size of open populations when detection probabilities and search coverages are less than 1. In this report, we outline the statistical models and data structures underlying the estimator. The models are numerous, complex, and intricately interwoven. Discussion begins with broad, high-level overviews of the general models. The lower-level technical details are then gradually added. Broader and less technical discussions on the general context and applications of the models and the use of the software are available in the software user guide (Simonis and others, 2018), vignettes bundled with the software, and the help files within the software itself.

Techniques and Methods↗
USGS2018

GenEst user guide—Software for a generalized estimator of mortality

GenEst (Generalized Estimator) is a software tool for estimating the total number of individuals arriving in an area during a specific time period when their detection probability is unknown but estimable. Its development was motivated by the need to accurately estimate the total number of bird and bat fatalities occurring at wind and solar energy facilities, but it is applicable in a variety of other contexts as well. Simple counts of carcasses are not an accurate measure of the true number of fatalities because some carcasses are inevitably missed in carcass searches. Furthermore, simple carcass counts do not allow comparison among locations or years because carcasses may be detected at different rates. This software uses data collected during carcass searches and estimates of detection rates to accurately estimate the number of fatalities and to provide a measure of precision associated with the estimate. These estimates are fundamental to understanding acute and cumulative effects of renewable energy development on wildlife populations. The software package is available with a user-friendly graphic interface as well as a flexible and powerful command-line implementation. GenEst includes tools for estimating searcher efficiency, carcass persistence, and other detection probability parameters from experimental field trials. Included in the software are example datasets for analyses, standard R package help files, this user guide, and vignettes detailing use at the command-line.

Techniques and Methods↗
USGS2018

Raptor interactions with wind energy: Case studies from around the world

The global potential for wind power generation is vast, and the number of installations is increasing rapidly. We review case studies from around the world of the effects on raptors of wind-energy development. Collision mortality, displacement, and habitat loss have the potential to cause population-level effects, especially for species that are rare or endangered. The impact on raptors has much to do with their behavior, so careful siting of wind-energy developments to avoid areas suited to raptor breeding, foraging, or migration would reduce these effects. At established wind farms that already conflict with raptors, reduction of fatalities may be feasible by curtailment of turbines as raptors approach, and offset through mitigation of other human causes of mortality such as electrocution and poisoning, provided the relative effects can be quantified. Measurement of raptor mortality at wind farms is the subject of intense effort and study, especially where mitigation is required by law, with novel statistical approaches recently made available to improve the notoriously difficult-to-estimate mortality rates of rare and hard-to-detect species. Global standards for wind farm placement, monitoring, and effects mitigation would be a valuable contribution to raptor conservation worldwide.

Journal of Raptor Research↗
USGS2017

Evidence of absence (v2.0) software user guide

Evidence of Absence software (EoA) is a user-friendly software application for estimating bird and bat fatalities at wind farms and for designing search protocols. The software is particularly useful in addressing whether the number of fatalities is below a given threshold and what search parameters are needed to give assurance that thresholds were not exceeded. The software also includes tools (1) for estimating carcass persistence distributions and searcher efficiency parameters (𝑝 and 𝑘 ) from field trials, (2) for projecting future mortality based on past monitoring data, and (3) for exploring the potential consequences of various choices in the design of long-term incidental take permits for protected species. The software was designed specifically for cases where tolerance for mortality is low and carcass counts are small or even 0, but the tools also may be used for mortality estimates when carcass counts are large.

Data Series↗
USGS2016

Mortality monitoring design for utility-scale solar power facilities

Introduction Solar power represents an important and rapidly expanding component of the renewable energy portfolio of the United States (Lovich and Ennen, 2011; Hernandez and others, 2014). Understanding the impacts of renewable energy development on wildlife is a priority for the U.S. Fish and Wildlife Service (FWS) in compliance with Department of Interior Order No. 3285 (U.S. Department of the Interior, 2009) to “develop best management practices for renewable energy and transmission projects on the public lands to ensure the most environmentally responsible development and delivery of renewable energy.” Recent studies examining effects of renewable energy development on mortality of migratory birds have primarily focused on wind energy (California Energy Commission and California Department of Fish and Game, 2007), and in 2012 the FWS published guidance for addressing wildlife conservation concerns at all stages of land-based wind energy development (U.S. Fish and Wildlife Service, 2012). As yet, no similar guidelines exist for solar development, and no published studies have directly addressed the methodology needed to accurately estimate mortality of birds and bats at solar facilities. In the absence of such guidelines, ad hoc methodologies applied to solar energy projects may lead to estimates of wildlife mortality rates that are insufficiently accurate and precise to meaningfully inform conversations regarding unintended consequences of this energy source and management decisions to mitigate impacts. Although significant advances in monitoring protocols for wind facilities have been made in recent years, there remains a need to provide consistent guidance and study design to quantify mortality of bats, and resident and migrating birds at solar power facilities (Walston and others, 2015). In this document, we suggest methods for mortality monitoring at solar facilities that are based on current methods used at wind power facilities but adapted for the unique conditions encountered at solar facilities. In particular, unlike at wind-power facilities, the unimpeded access to almost all areas within the facilities, the typically flat terrain, and general absence of thick vegetation allow distance-sampling techniques (Buckland and others, 2001, 2004) to be exploited to advantage at industrial solar sites. These protocols build on the work of Nicolai and others (2011), and as our understanding and techniques for monitoring improve, the methods may be further modified to incorporate improvements in the future. We present case studies based on monitoring methods currently implemented at different utility-scale solar facilities to illustrate how distance-sampling techniques may improve overall detectability without substantially increasing costs. Every facility is unique, and the protocols presented may be adapted based on specific monitoring objectives and conditions at each site. We provide guidance for designing monitoring programs whose objective it is to estimate the total number of bird and bat fatalities occurring at a facility over an extended period of time. We address spatial variation in causes of mortality, as well as potential sources of imperfect detection, for example, animals falling in or moving to unsearched areas, carcasses removed by predators, and carcasses missed by searchers. We suggest methods to estimate and account for each source of imperfect detection. This document focuses on monitoring design only and does not discuss approaches for estimating mortality from collected data. The development of statistically sound estimators relevant to the solar context is a current topic of research, although there are already strong foundations for estimation with distance-sampling methods in similar open, arid environments (Anderson and others, 2001; Freilich and others, 2005). Nonetheless, if protocols described in this document are followed, the resulting data will be adequate and sufficient for estimating mortality using newly formulated estimators.

Open-File Report↗
USGS2016

Wind energy development: Methods to assess bird and bat fatality rates post-construction

Monitoring fatalities at wind energy facilities after they have been constructed can provide valuable information regarding impacts of wind power development on wildlife. The objective of this monitoring is to estimate abundance of a super-population of carcasses that entered the area within a designated period of time. By definition, the population is not closed and carcasses can enter as they are killed through collision with turbines, and leave as they are removed by scavengers or decompose to a point where they are not recognizable. In addition, the population is not inherently mobile, but can only change location through some external force. A focus on number of animal carcasses comprising the super-population, combined with peculiar traits that resist classic assumptions, distinguish fatality estimation at wind-power facilities from more classic abundance estimates that can be addressed through mark-recapture techniques or other well-known abundance estimators. We review the available methods to estimate the super-population of carcasses at wind power facilities. We discuss the role of these estimates in determining appropriate levels of minimization and mitigation of impacts to individual species of concern. We discuss the potential to extrapolate these measurements to reflect the cumulative effect of the industry on individual species. Finally, we suggest avenues of research needed to strengthen our understanding of the effect wind power development has, and might have in the future, on wildlife on this continent and worldwide.

Human-Wildlife Interactions↗
USGS2015

A framework for decision points to trigger adaptive management actions in long-term incidental take permits

Introduction The U.S. Fish and Wildlife Service (USFWS) has begun to issue incidental take permits (ITPs) to wind power companies to allow limited take of bird and bat species that are protected under the Endangered Species Act, the Bald and Golden Eagle Protection Act, or the Migratory Bird Treaty Act (Huso and others, 2015). Expected take rates are determined using scientifically based collision-risk models and knowledge about the ecology of the population of interest. ITPs often include mitigation requirements to compensate for estimated take and further describe (1) adaptive management actions (AMAs) that may be required to reduce take rates if permitted rate is exceeded, or (2) additional compensatory mitigation to offset take that exceeds permitted levels. Confirming the accuracy of predicted take and providing evidence that permitted take levels have not been exceeded can be challenging because carcasses may be detected with probability much less than 1, and often no carcasses are observed. When detection probability is high, finding 0 carcasses can be interpreted as evidence that none (or few) were actually killed. As the probability of observing an individual decreases, the likelihood of missing carcasses increases, making it unclear how to interpret having observed 0 (or few) carcasses. In a practical sense, the consequences of incorrect inference can be significant: overestimating take could result in costly and unjustified mitigation, whereas underestimating could result in unanticipated declines in species populations already at risk.

Open-File Report↗
USGS2014

Behavior of bats at wind turbines

Wind turbines are causing unprecedented numbers of bat fatalities. Many fatalities involve tree-roosting bats, but reasons for this higher susceptibility remain unknown. To better understand behaviors associated with risk, we monitored bats at three experimentally manipulated wind turbines in Indiana, United States, from July 29 to October 1, 2012, using thermal cameras and other methods. We observed bats on 993 occasions and saw many behaviors, including close approaches, flight loops and dives, hovering, and chases. Most bats altered course toward turbines during observation. Based on these new observations, we tested the hypotheses that wind speed and blade rotation speed influenced the way that bats interacted with turbines. We found that bats were detected more frequently at lower wind speeds and typically approached turbines on the leeward (downwind) side. The proportion of leeward approaches increased with wind speed when blades were prevented from turning, yet decreased when blades could turn. Bats were observed more frequently at turbines on moonlit nights. Taken together, these observations suggest that bats may orient toward turbines by sensing air currents and using vision, and that air turbulence caused by fast-moving blades creates conditions that are less attractive to bats passing in close proximity. Tree bats may respond to streams of air flowing downwind from trees at night while searching for roosts, conspecifics, and nocturnal insect prey that could accumulate in such flows. Fatalities of tree bats at turbines may be the consequence of behaviors that evolved to provide selective advantages when elicited by tall trees, but are now maladaptive when elicited by wind turbines.

Indiana↗
USGS2014

Region-wide ecological responses of arid Wyoming big sagebrush communities to fuel treatments

If arid sagebrush ecosystems lack resilience to disturbances or resistance to annual invasives, then alternative successional states dominated by annual invasives, especially cheatgrass ( Bromus tectorum L.), are likely after fuel treatments. We identified six Wyoming big sagebrush ( Artemisia tridentata ssp. wyomingensis Beetle & Young) locations (152–381 mm precipitation) that we believed had sufficient resilience and resistance for recovery. We examined impacts of woody fuel reduction (fire, mowing, the herbicide tebuthiuron, and untreated controls, all with and without the herbicide imazapic) on short-term dominance of plant groups and on important land health parameters with the use of analysis of variance (ANOVA). Fire and mowing reduced woody biomass at least 85% for 3 yr, but herbaceous fuels were reduced only by fire (72%) and only in the first year. Herbaceous fuels produced at least 36% more biomass with mowing than untreated areas during posttreatment years. Imazapic only reduced herbaceous biomass after fires (34%). Tebuthiuron never affected herbaceous biomass. Perennial tall grass cover was reduced by 59% relative to untreated controls in the first year after fire, but it recovered by the second year. Cover of all remaining herbaceous groups was not changed by woody fuel treatments. Only imazapic reduced significantly herbaceous cover. Cheatgrass cover was reduced at least 63% with imazapic for 3 yr. Imazapic reduced annual forb cover by at least 45%, and unexpectedly, perennial grass cover by 49% (combination of tall grasses and Sandberg bluegrass [ Poa secunda J. Presl.]). Fire reduced density of Sandberg bluegrass between 40% and 58%, decreased lichen and moss cover between 69% and 80%, and consequently increased bare ground between 21% and 34% and proportion of gaps among perennial plants > 2 m (at least 28% during the 3 yr). Fire, mowing, and imazapic may be effective in reducing fuels for 3 yr, but each has potentially undesirable consequences on plant communities.

Wyoming↗
USGS2013

Habitat selection by juvenile Swainson’s thrushes ( Catharus ustulatus ) in headwater riparian areas, northwestern Oregon, USA

Lower order, non-fish-bearing streams, often termed “headwater streams”, have received minimal research effort and protection priority, especially in mesic forests where distinction between riparian and upland vegetation can be subtle. Though it is generally thought that breeding bird abundance is higher in riparian zones, little is known about species distributions when birds are in their juvenile stage – a critical period in terms of population viability. Using radio telemetry, we examined factors affecting habitat selection by juvenile Swainson’s thrushes during the post-breeding period in headwater basins in the Coast Range of Oregon, USA. We tested models containing variables expected to influence the amount of food and cover (i.e., deciduous cover, coarse wood volume, and proximity to stream) as well as models containing variables that are frequently measured and manipulated in forest management (i.e., deciduous and coniferous trees separated into size classes). Juvenile Swainson’s thrushes were more likely to select locations with at least 25% cover of deciduous, mid-story vegetation and more than 2.0 m 3 /ha of coarse wood within 40 m of headwater streams. We conclude that despite their small and intermittent nature, headwater streams and adjacent riparian areas are selected over upland areas by Swainson’s thrush during the postfledging period in the Oregon Coast Range.

Oregon↗
USGS2013

Estimating direct fatality impacts at wind farms: how far we’ve come, where we have yet to go

Measuring the potential impacts of wind farms on wildlife can be difficult and may require development of new statistical tools and models to accurately reflect the measurement process. This presentation reviews the recent history of approaches to estimating wildlife fatality under the unique conditions encountered at wind farms, their unifying themes and their potential shortcomings. Avenues of future research are suggested to continue to address the needs of resource managers and industry in understanding direct impacts of wind turbine-caused wildlife fatality.

Conference Paper↗
USGS2012

Fatality estimator user’s guide

This publication is the User's Guide for software developed to estimate wildlife fatalities at wind-power facilities, although the software is applicable to a variety of circumstances in which the objective is to estimate the size of a superpopulation and the probability of detection of the individuals is less than one. Simple counts of carcasses do not accurately reflect fatality and do not allow comparison among locations because carcasses may be detected at different rates. This software uses data collected during carcass searches and knowledge of detection rates to accurately estimate the number of fatalities and to provide a measure of precision associated with the estimate. These estimates are fundamental to understanding acute and cumulative effects of wind power on wildlife populations. Only carcasses judged to have been killed after the previous search should be included in the fatality data set submitted to this estimator software. This estimator already corrects for carcasses missed in previous searches, so carcasses judged to have been missed at least once should be considered “incidental” and not included in the fatality data set used to estimate fatality. Note: When observed carcass count is <5 (including 0 for species known to be at risk, but not observed), USGS Data Series 881 ( https://pubs.usgs.gov/ds/0881/ ) is recommended for fatality estimation.

Data Series↗