Geology topics

James E. Diffendorfer

Publications and source records attributed to James E. Diffendorfer.

At least 37 records · Page 2Linked to original sources

USGS2022

Wind turbine wakes can impact down-wind vegetation greenness

Global wind energy has expanded 5-fold since 2010 and is predicted to expand another 8–10-fold over the next 30 years. Wakes generated by wind turbines can alter downwind microclimates and potentially downwind vegetation. However, the design of past studies has made it difficult to isolate the impact of wake effects on vegetation from land cover change. We used hourly wind data to model wake and non-wake zones around 17 wind facilities across the U.S. and compared remotely-sensed vegetation greenness in wake and non-wake zones before and after construction. We located sampling sites only in the dominant vegetation type and in areas that were not disturbed before or after construction. We found evidence for wake effects on vegetation greenness at 10 of 17 facilities for portions of, or the entire growing season. Evidence included statistical significance in Before After Control Impact statistical models, differences >3% between expected and observed values of vegetation greenness, and consistent spatial patterns of anomalies in vegetation greenness relative to turbine locations and wind direction. Wakes induced both increases and decreases in vegetation greenness, which may be difficult to predict prior to construction. The magnitude of wake effects depended primarily on precipitation and to a lesser degree aridity. Wake effects did not show trends over time following construction, suggesting the changes impact vegetation greenness within a growing season, but do not accrue over years. Even small changes in vegetation greenness, similar to those found in this study, have been seen to affect higher trophic levels. Given the rapid global growth of wind energy, and the importance of vegetation condition for agriculture, grazing, wildlife, and carbon storage, understanding how wakes from wind turbines impact vegetation is essential to exploit or ameliorate these effects.

Environmental Research Letters↗

USGS2022

Using ecosystem services to identify inequitable outcomes in migratory species conservation

Biodiversity conservation efforts have been criticized for generating inequitable socio-economic outcomes. These equity challenges are largely analyzed as place-based problems affecting local communities directly impacted by conservation programs. The conservation of migratory species extends this problem geographically since people in one place may benefit while those in another bear the costs of conservation. The spatial subsidies approach offers an effective tool for analyzing such relationships between places connected by migratory species. Designed to quantify ecosystem services provided and received in specific locations across a migratory species’ range—and the disparities between them—the spatial subsidies approach highlights three axes of inequity: between indigenous and settler colonial societies, between urban and rural populations, and between the Global North and Global South. Recognizing these relationships is critical to achieving two mutually reinforcing policy goals: avoiding inequitable conservation outcomes in efforts to conserve migratory species, and ensuring effective long-term conservation of migratory species. In demonstrating how the spatial subsidies approach enables the identification and quantification of inequities involving three migratory species (northern pintail ducks, monarch butterflies, and Mexican free-tailed bats), we argue that a spatial subsidies approach could apply to migratory species conservation efforts worldwide under the context of “payments for ecosystem services.”

Conservation Letters↗

USGS2022

Vulnerability of avian populations to renewable energy production

Renewable energy production can kill individual birds, but little is known about how it affects avian populations. We assessed the vulnerability of populations for 23 priority bird species killed at wind and solar facilities in California, USA. Bayesian hierarchical models suggested that 48% of these species were vulnerable to population-level effects from added fatalities caused by renewables and other sources. Effects of renewables extended far beyond the location of energy production to impact bird populations in distant regions across continental migration networks. Populations of species associated with grasslands where turbines were located were most vulnerable to wind. Populations of nocturnal migrant species were most vulnerable to solar, despite not typically being associated with deserts where the solar facilities we evaluated were located. Our findings indicate that addressing declines of North American bird populations requires consideration of the effects of renewables and other anthropogenic threats on both nearby and distant populations of vulnerable species.

California↗

USGS2022

Multi-species, multi-country analysis reveals North Americans are willing to pay for transborder migratory species conservation

Migratory species often provide ecosystem service benefits to people in one country while receiving habitat support in other countries. The multinational cooperation that could help ensure continued provisioning of these benefits by migration may be informed by understanding the economic values people in different countries place on the benefits they derive from migratory wildlife. We conducted contingent valuation surveys to estimate the willingness of 3733 respondents from Canada, the United States and México to invest in conservation for two disparate migratory species, the northern pintail duck Anas acuta and the Mexican free-tailed bat Tadarida brasiliensis mexicana . With zero-inflated mixed-effects negative binomial regression (explaining 87% of the variation in willingness to pay for conservation), we found that respondents from each nation, after controlling for both household income and per capita national Gross Domestic Product, were willing to invest in conservation in other countries. This willingness to pay for conservation, even when respondents knew that funds would be used to support benefits accruing primarily in other countries, demonstrates the potential for support of multinational conservation policies and programmes that direct resources to locations where the most critical habitat is located, rather than where the funding is generated. These findings could be used to support the development or expansion of new and existing international conservation programmes for migratory species.

People and Nature↗

USGS2022

Urban landcover differentially drives day and nighttime air temperature across a semi-arid city

Semi-arid urban environments are undergoing an increase in both average air temperatures and in the frequency and intensity of extreme heat events. Within cities, different composition and densities of urban landcovers (ULC) influence local air temperatures, either mitigating or increasing heat. Currently, understanding how combinations of ULC influence air temperature at the block to neighborhood scale is necessary for heat mitigation plans, and yet limited due to the complexities integrating high-resolution ULC with spatial and temporally high-resolution microclimate data. We quantify how ULC influences air temperature at 60 m resolution for day and nighttime climate normals and extreme heat conditions by integrating microclimate sensor data sensor and high-resolution (1 m 2 ) ULC for Denver, Colorado's urban core. We derive ULC drivers of air temperature using a structural equation model, then use a random forest algorithm to predict air temperatures for 30-year climate normals and an extreme heat condition. We find that, in conjunction with other ULC, urban tree canopy reduces daytime air temperatures (−0.026 °C per % cover), and the combination of impervious surfaces and buildings increases daytime air temperature (0.021 °C per % cover). Compared to daytime hours, nighttime irrigated turf temperature cooling effects are increased from being non-significant to −0.022 °C per % cover, while tree canopy effects are reduced from −0.026 °C during the day to −0.016 °C at night. Overall, ULC drives ~17% and 25% of local air temperature during the day and night, respectively. ULC influence on daytime air temperatures is altered in extreme heat events, both depending on the ULC type and time of day. Our findings inform urban planners seeking to identify potential hot and cool spots within a semi-arid city and mitigate high urban air temperatures through using ULC within larger urban climate mitigation strategies.

Colorado↗

USGS2021

Demographic and potential biological removal models identify raptor species sensitive to current and future wind energy

A central challenge in applied ecology is understanding the effect of anthropogenic fatalities on wildlife populations and predicting which populations may be particularly vulnerable and in greatest need of management attention. We used 3 approaches to investigate potential effects of fatalities from collisions with wind turbines on 14 raptor species for both current (106 GW) and anticipated future (241 GW) levels of installed wind energy capacity in the United States. Our goals were to identify species at relatively high vs low risk of experiencing population declines from turbine collisions and to also compare results generated from these approaches. Two of the approaches used a calculated turbine-caused mortality rate to decrement population growth, where population trends were derived either from the North American Breeding Bird Survey or a matrix model parameterized from literature-derived demographic values. The third approach was potential biological removal, which estimates the number of fatalities that allow a population to reach and maintain its optimal sustainable population set by management concerns. Different results among the methods reveal substantial gaps in knowledge and uncertainty in both demographic parameters and species-specific estimates of fatalities from wind turbines. Our results suggest that, of the 14 species studied, those with relatively higher potential of population-level impacts from wind turbine collisions included barn owl, ferruginous hawk, golden eagle, American kestrel, and red-tailed hawk. Burrowing owl, Cooper’s hawk, great horned owl, northern harrier, turkey vulture, and osprey had a relatively lower potential for population impacts, and results were not easily interpretable for merlin, prairie falcon, and Swainson’s hawk. Projections of current levels of fatalities to future wind energy scenarios at 241 GW of installed capacity suggest some species could experience population declines because of turbine collisions. Populations of those species may benefit from research to identify tools to prevent or reduce raptor collisions with wind turbines.

Ecosphere↗

USGS2021

TrendPowerTool: A lookup tool for estimating the statistical power of a monitoring program to detect population trends

A simulation-based power analysis can be used to estimate the sample sizes needed for a successful monitoring program, but requires technical expertise and sometimes extensive computing resources. We developed a web-based lookup app, called TrendPowerTool ( https://www.usgs.gov/apps/TrendPowerTool/ ), to provide guidance for ecological monitoring programs when resources are not available for a simulation-based power analysis. TrendPowerTool is implemented through the shiny package in R, but is accessible through a webpage without the need for users to install any software. By drawing on results of 1.4 million scenarios that we simulated on a supercomputer, TrendPowerTool quickly and easily provides an estimate of the statistical power to detect a population trend of a particular magnitude with a planned monitoring program, based on user-specified parameters for the monitoring design and population of interest. TrendPowerTool provides a user-friendly interface that retrieves results instantaneously, facilitating the important step of conducting a power analysis when designing monitoring programs.

Conservation Science and Practice↗

USGS2020

Editorial: North American monarch butterfly ecology and conservation

Spanning Canada, the United States, and Mexico, North America contains two populations of the migratory monarch butterfly ( Danaus plexippus ). The smaller “western” population overwinters in groves along the California coast and breeds west of the Rocky Mountains, while the much larger “eastern” population breeds east of the Rocky Mountains and overwinters in Oyamel fir forests in central Mexico. Both populations have declined in the last 20 to 30 years, leading to a formal petition in 2014 to list the species as threatened or endangered under the US Endangered Species Act (ESA) and a recommendation in 2016 for listing as endangered under the Canadian Species at Risk act.

Frontiers in Ecology and Conservation↗

USGS2020

Limitations, lack of standardization, and recommended best practices in studies of renewable energy effects on birds and bats

Increasing global energy demand is fostering the development of renewable energy as an alternative to fossil fuels. However, renewable energy facilities may adversely affect wildlife. Facility siting guidelines recommend or require project developers complete pre‐ and postconstruction wildlife surveys to predict risk and estimate effects of proposed projects. Despite this, there are no published studies that have quantified the types of surveys used or how survey types are standardized within and across facilities. We evaluated 628 peer‐reviewed publications, unpublished reports, and citations, and we analyzed data from 525 of these sources (203 facilities: 193 wind and 10 solar) in the United States and Canada to determine the frequency of pre‐ and postconstruction surveys and whether that frequency changed over time; frequency of studies explicitly designed to allow before‐after or impact‐control analyses; and what types of survey data were collected during pre‐ and postconstruction periods and how those data types were standardized across periods and among facilities. Within our data set, postconstruction monitoring for wildlife fatalities and habitat use was a standard practice ( n = 446 reports), but preconstruction estimation of baseline wildlife habitat use and mortality was less frequently reported ( n = 84). Only 22% ( n = 45) of the 203 facilities provided data from both pre‐ and postconstruction, and 29% ( n = 59) had experimental study designs. Of 108 facilities at which habitat‐use surveys were conducted, only 3% estimated of detection probability. Thus, the available data generally preclude comparison of biological data across construction periods and among facilities. Use of experimental study designs and following similar field protocols would improve the knowledge of how renewable energy affects wildlife.

Conservation Biology↗

USGS2020

Assessing population-level consequences of anthropogenic stressors for terrestrial wildlife

Human activity influences wildlife. However, the ecological and conservation significances of these influences are difficult to predict and depend on their population‐level consequences. This difficulty arises partly because of information gaps, and partly because the data on stressors are usually collected in a count‐based manner (e.g., number of dead animals) that is difficult to translate into rate‐based estimates important to infer population‐level consequences (e.g., changes in mortality or population growth rates). However, ongoing methodological developments can provide information to make this transition. Here, we synthesize tools from multiple fields of study to propose an overarching, spatially explicit framework to assess population‐level consequences of anthropogenic stressors on terrestrial wildlife. A key component of this process is using ecological information from affected animals to upscale from count‐based field data on individuals to rate‐based demographic inference. The five steps to this framework are (1) framing the problem to identify species, populations, and assessment parameters; (2) field‐based measurement of the effect of the stressor on individuals; (3) characterizing the location and size of the populations of interest; (4) demographic modeling for those populations; and (5) assessing the significance of stressor‐induced changes in demographic rates. The tools required for each of these steps are well developed, and some have been used in conjunction with each other, but the entire group has not previously been unified together as we do in this framework. We detail these steps and then illustrate their application for two species affected by different anthropogenic stressors. In our examples, we use stable hydrogen isotope data to infer a catchment area describing the geographic origins of affected individuals, as the basis to estimate population size for that area. These examples reveal unexpectedly greater potential risks from stressors for the more common and widely distributed species. This work illustrates key strengths of the framework but also important areas for subsequent theoretical and technical development to make it still more broadly applicable.

Ecosphere↗

USGS2020

Is your ad hoc model selection strategy affecting your multimodel inference?

(Yackulic) 1. Ecologists routinely fit complex models with multiple parameters of interest, where hundreds or more competing models are plausible. To limit the number of fitted models, ecologists often define a model selection strategy composed of a series of stages in which certain features of a model are compared while other features are held constant. Defining these multi-stage strategies requires making a series of decisions, which may potentially impact inferences, but have not been critically evaluated. 2. We begin by identifying key features of strategies, introducing descriptive terms when they did not already exist in the literature. Strategies differ in how they define and order model building stages. Sequential-by-sub-model strategies focus on one sub-model (parameter) at a time with modeling of subsequent sub-models dependent on the selected model structures from the previous stages. Secondary candidate set strategies model sub-models independently and combine the top set of models from each sub-model for selection in a final stage. Build-up approaches define stages across sub-models and increase in complexity at each stage. Strategies also differ in how the top set of models is selected in each stage and whether they use null or more complex model structures for non-target sub-models. 3. We tested the performance of different model selection strategies using four datasets and three model types. For each dataset, we determined the “true” distribution of AIC weights by fitting all plausible models. Then, we calculated the number of models that would have been fitted and the portion of “true” AIC weight we recovered under different model selection strategies. 4. Sequential-by-sub-model strategies often performed poorly. Build-up or secondary candidate sets were more reliable, provided all models within 5 AIC of the top model were carried forward to subsequent stages. The structure of non-target sub-models was less important. 5. Multi-stage approaches cannot compensate for a lack of critical thought in selecting covariates and building models to represent competing a priori hypotheses. However, even when competing hypotheses for different sub-models are limited, thousands or more models may be possible so strategies to explore candidate model space reliably and efficiently will be necessary.

Ecosphere↗

USGS2020

A continuously updated, geospatially rectified database of utility-scale wind turbines in the United States

Nearly 60,000 utility-scale wind turbines are installed in the United States as of July, 2019, representing over 97 gigawatts of electric power capacity; US wind turbine installations continue to grow at a rapid pace. Yet, until April 2018, no publicly-available, regularly updated data source existed to describe those turbines and their locations. Under a cooperative research and development agreement, analysts from three organizations collaborated to develop and release the United States Wind Turbine Database (USWTDB) - a publicly available, continuously updated, spatially rectified data source of locations and attributes of utility-scale wind turbines in the United States. Technical specifications and wind facility data, incorporated from five sources, undergo rigorous quality control. The location of each turbine is visually verified using high-resolution aerial imagery. The quarterly-updated data are available in a variety of formats, including an interactive web application, comma-separated values (CSV), shapefile, and application programming interface (API). The data are used widely by academic researchers, engineers and developers from wind energy companies, government agencies, planners, educators, and the general public.

Scientific Data↗

USGS2020

Challenges for leveraging citizen science to support statistically robust monitoring programs

Large samples and long time series are often needed for effective broad-scale monitoring of status and trends in wild populations. Obtaining those sample sizes can be more feasible when volunteers contribute to the dataset, but volunteer-selected sites are not always representative of a population. Previous work to account for biased site selection has relied on knowledge of covariates to explain differences between site types, but such knowledge is often unavailable. For cases where relevant covariates have not been defined, we used a simulation study to identify the consequences of including non-probabilistically selected sites (NP sites) in addition to sites selected from a probability-based design (P sites), test modeling frameworks that might correct for biases, and evaluate whether those frameworks could allow NP sites to reduce the sampling requirement for P sites and potentially reduce costs of monitoring. We informed the simulation with pilot data from surveys of monarch butterflies and their obligate larval host plant, milkweed. We found strong biases in NP sites versus P sites in density and trends of monarchs and milkweed. Modeling frameworks that accounted for site type with a group effect or that strongly downweighted NP sites successfully produced unbiased estimates. However, sampling more NP sites typically did not improve accuracy or precision, and adding NP sites sometimes required also adding P sites to prevent biases. Further work on novel modeling frameworks would be useful to allow citizen-science data to contribute useful information to conservation.

Biological Conservation↗

USGS2020

Quantifying the contribution of habitats and pathways to a spatially structured population facing environmental change

The consequences of environmental disturbance and management are difficult to quantify for spatially structured populations because changes in one location carry through to other areas as a result of species movement. We develop a metric, G , for measuring the contribution of a habitat or pathway to network-wide population growth rate in the face of environmental change. This metric is different from other contribution metrics, as it quantifies effects of modifying vital rates for habitats and pathways in perturbation experiments. Perturbation treatments may range from small degradation or enhancement to complete habitat or pathway removal. We demonstrate the metric using a simple metapopulation example and a case study of eastern monarch butterflies. For the monarch case study, the magnitude of environmental change influences the ordering of node contribution. We find that habitats within which all individuals reside during one season are the most important to short-term network growth under complete removal scenarios, whereas the central breeding region contributes most to population growth over all but the strongest disturbances. The metric G provides for more efficient management interventions that proactively mitigate impacts of expected disturbances to spatially structured populations. use changes in one location carry through to other areas due to species movement. We develop a metric, G, for measuring the contribution of a habitat or pathway to network-wide population growth rate in the face of environmental change. This metric is different than other contribution metrics as it quantifies effects of modifying vital rates for habitats and pathways in perturbation experiments. Perturbation treatments may range from small degradation or enhancement to complete habitat or pathway removal. We demonstrate the metric using a simple metapopulation example and a case study of eastern monarch butterflies. For the monarch case study, the magnitude of environmental change influences ordering of node contribution. We find that habitats through which all migrants flow are the most important to short-term network growth under complete-removal scenarios. The metric G provides for more efficient management interventions that proactively mitigate impacts of expected disturbances to spatially structured populations.

American Naturalist↗

USGS2020

Learning from real-world experience to understand renewable energy impacts to wildlife

The project team sought to use real-world data to understand adverse effects to wildlife of renewable energy production that is critical to meeting California’s climate and clean energy goals. The project had three main components. First, a systematic literature review studied 20 peer-reviewed publications and 612 reports from other nonreviewed sources from 231 wind and solar facilities in North America. Within California, 50 percent of facilities collected pre- and post-construction data, 30 percent had experimental study designs, and fewer than 7 percent estimated detection probability during habitat use surveys. Mitigation at wind power plants focused on repowering to reduce risk to soaring birds and at solar facilities emphasized wildlife deterrence and compensatory mitigation. Second, the authors developed a best-practices approach to employ environmental isotopes (for example, hydrogen obtained from animal tissue) and rescaling functions (a statistical approach to modeling the relationship between variables) to assign individual birds or bats to their place of origin. The team applied this approach to feathers from 411 individuals of 12 species killed at wind facilities and 515 individuals of 19 species killed at solar facilities. From 24 percent to 100 percent (mean +/- SD = 49 percent +/- 33 percent) and 25 percent to 100 percent (73 percent +/- 25 percent) of birds grew feathers at a location outside the collection site at wind and solar facilities, respectively. Third, the authors constructed Bayesian integrated population models (probability models) for 29 focal species affected by wind or solar energy generation in California. Species predominantly local in origin generally had lower population growth rates than did species that were predominantly nonlocal in origin. These patterns illustrate the complex linkages between behavioral ecology, vulnerability to mortality, and population-level impacts to wildlife from fatalities at renewable energy facilities. This project benefits the renewable energy sector by providing a framework and specific tools for understanding environmental impacts of renewable energy generation.

California↗

USGS2019

Is the timing, pace and success of the monarch migration associated with sun angle?

A basic question concerning the monarch butterfly’s fall migration is which monarchs succeed in reaching overwintering sites in Mexico, which fail—and why. We document the timing and pace of the fall migration, ask whether the sun’s position in the sky is associated with the pace of the migration, and whether timing affects success in completing the migration. Using data from the Monarch Watch tagging program, we explore whether the fall monarch migration is associated with the daily maximum vertical angle of the sun above the horizon (Sun Angle at Solar Noon, SASN) or whether other processes are more likely to explain the pace of the migration. From 1998 to 2015, more than 1.38 million monarchs were tagged and 13,824 (1%) were recovered in Mexico. The pace of migration was relatively slow early in the migration but increased in late September and declined again later in October as the migrating monarchs approached lower latitudes. This slow-fast-slow pacing in the fall migration is consistent with monarchs reaching latitudes with the same SASN, day after day, as they move south to their overwintering sites. The observed pacing pattern and overall movement rates are also consistent with monarchs migrating at a pace determined by interactions among SASN, temperature, and daylength. The results suggest monarchs successfully reaching the Monarch Butterfly Biosphere Reserve (MBBR) migrate within a “migration window” with an SASN of about 57° at the leading edge of the migration and 46° at the trailing edge. Migrants reaching locations along the migration route with SASN outside this migration window may be considered early or late migrants. We noted several years with low overwintering abundance of monarchs, 2004 and 2011–2014, with high percentages of late migrants. This observation suggests a possible effect of migration timing on population size. The migration window defined by SASN might serve as a framework against which to establish the influence of environmental factors on the size, geographic distribution, and timing of past and future fall migrations.

Frontiers in Ecology and Evolution↗

USGS2019

Challenges for monitoring the extent and land use/cover changes in monarch butterflies’ migratory habitat across the United States and Mexico

This paper presents a synopsis of the challenges and limitations presented by existing and emerging land use/ land cover (LULC) digital data sets when used to analyze the extent, habitat quality, and LULC changes of the monarch (Danaus plexippus) migratory habitat across the United States of America (US) and Mexico. First, the characteristics, state of the knowledge, and issues related to this habitat are presented. Then, the characteristics of the existing and emerging LULC digital data sets with global or cross-border coverage are listed, followed by the data sets that cover only the US or Mexico. Later, we discuss the challenges for determining the extent, habitat quality, and LULC changes in the monarchs’ migratory habitat when using these LULC data sets in conjunction with the current state of the knowledge of the monarchs’ ecology, behavior, and foraging/roosting plants used during their migration. We point to approaches to address some of these challenges, which can be categorized into: (a) LULC data set characteristics and availability; (b) availability of ancillary land management information; (c) ability to construct accurate forage suitability indices for their migration habitat; and (d) level of knowledge of the ecological and behavioral patterns of the monarchs during their journey.

Land↗

USGS2019

Review of indicators for comparing environmental effects across energy sources

Robust, quantitative comparisons of environmental effects across energy sources can support development of energy planning strategies that meet growing demand while managing and minimizing undesirable effects on environmental resources. Multicriteria analyses of energy systems often use a suite of indicators to make such comparisons, but those indicators and their units of measure vary among studies. We reviewed 179 papers that described or applied energy indicators to compare environmental effects of different primary energy sources to answer four questions: (1) what environmental indicators have been used in multicriteria energy-source comparisons? (2) across studies, how consistently are these indicators used to quantify effects? (3) to what degree are different effects accounted for across energy sources and locations? and (4) how comprehensive are indicators in terms of assessing known environmental effects? For reviewed studies, we quantified the number of unique indicators and the diversity of indicators used to measure different effects. We also recorded the specific measurement units applied to quantify each indicator, the energy sources evaluated, and the continent where each study was conducted. While we found that many environmental effects of energy development have been analyzed across multiple sources, indicators were frequently measured, interpreted, and applied in ways that are not directly comparable, and some known environmental effects were infrequently assessed. We also found an emphasis on applying indicators to renewable energy sources; assessing current and potential energy sources, both renewable and nonrenewable, would greatly clarify the full suite of tradeoffs among sources and can inform energy development strategies that minimize adverse environmental effects. Overall, our review indicated that making comprehensive comparisons of the effects of energy development across sources may require efforts to standardize how effects are measured, synthesize effects literature into an open-source database, expand the range of environmental effects analyzed, and establish consistent frameworks for comparison.

Environmental Research Letters↗