Geology topics

Jay E. Diffendorfer

Publications and source records attributed to Jay E. Diffendorfer.

At least 19 recordsLinked to original sources

USGS2026

Does wind disrupt overwintering monarch butterfly clusters? An observational study of western monarchs

Wind protection is a central focus of western monarch butterfly ( Danaus plexippus ) overwintering habitat conservation. The Wind Disruption Hypothesis guiding management decisions predicts that winds at or above 2 m/s disrupt clusters and that cluster abundance decreases as wind speed increases. At two California groves during the 2023–2024 overwintering season, we paired time-lapse estimates of visible cluster size with nearby measurements of maximum wind gust. Stronger gusts were not consistently followed by decreases over 30-min or next-day response windows. In the 30-min analysis, the wind association depended on approximate local temperature and whether visible butterflies were in direct sunlight. Stronger gusts were associated with declines under cool, sunny conditions and increases under warm, sunny conditions. No clear wind association was detected when no visible butterflies were in direct sunlight. The next-day analysis likewise indicated that the wind association varied with sun exposure. Nearby maximum gusts did not measure sustained exposure at butterfly positions, so this was not an exact test of the historical threshold. The results did not support the predicted consistent decline with increasing wind under the monitored conditions. Physiological responses to interacting wind, ambient temperature, and solar exposure offer a plausible hypothesis for future research.

California↗

USGS2026

Evaluating interactive effects of the Conservation Reserve Program and wind energy infrastructure on grassland bird abundance in the United States

The extent of grasslands has contracted globally, leading to significant declines in grassland-obligate species, including birds. Grassland birds are threatened by multiple factors, including grassland conversion to cropland, and development, including energy infrastructure. In the USA, the federal Conservation Reserve Program (CRP) provides financial incentives for agricultural landowners to convert marginal cropland to vegetative covers, including grassland, making it a key approach to recovering grasslands. However, given the high percentage of wind turbines near Conservation Reserve Program land, it is critical to determine if wind energy and the Conservation Reserve Program interact to affect grassland birds. We used generalized additive models and community science eBird data to assess the interactive effects of wind and the Conservation Reserve Program on the abundances of 27 grassland-obligate bird species across their breeding ranges in the continental US. We found associations between bird relative abundances and interactions involving wind and Conservation Reserve Program variables, suggesting that wind energy development near Conservation Reserve Program fields could dampen the benefits of the Conservation Reserve Program for some species. These results indicate that decisions about where to install wind energy infrastructure that incorporate information about the presence of Conservation Reserve Program land may reduce the adverse effects of wind energy on grassland birds. This study provides information that can help maximize the benefits of the Conservation Reserve Program while allowing for environmentally friendly development of renewable energy.

contiguous United States↗

USGS2026

What we know about wildlife outcomes of the conservation reserve program: A meta-analysis

The Conservation Reserve Program (CRP) is one of the most extensive private-land conservation programs in the United States, aimed at mitigating habitat loss and supporting biodiversity in agricultural landscapes. Individual studies of CRP effects on wildlife report mixed results, necessitating a comprehensive synthesis. We conducted a meta-analysis and vote-counting assessment of 96 studies (1009 case studies, i.e., individual analyses of a wildlife response to a CRP predictor variable) to evaluate effects on wildlife density, occurrence, reproduction, habitat use, and species diversity. Formal meta-analyses were performed for wildlife density and avian nest success. We found CRP generally benefited wildlife, with vote counting indicating positive effects in 32% of all comparisons (i.e., including comparisons to any type of non-CRP land) and in 64% of comparisons to cropland. Formal meta-analysis indicated avian nest success was significantly higher on CRP lands compared to non-CRP lands, but CRP enrollment did not consistently increase wildlife density, likely due to species-specific and ecological factors we did not account for. The literature was strongly biased toward birds (90% of case studies), with limited research on mammals, invertebrates, amphibians, and reptiles. High heterogeneity in effect sizes suggests that variation in conservation practices, study methodologies, and ecological contexts plays a critical role in shaping measured wildlife responses to CRP. Our results demonstrate CRP provides important benefits to wildlife, particularly by enhancing avian reproductive success. However, variation in wildlife effects highlights the need for studies that incorporate more detailed information on CRP management practices and increased research on non-avian taxa. Addressing these gaps may provide additional information allowing for the implementation of improved conservation strategies and maximize CRP's ecological benefits in agricultural landscapes.

Conservation Science and Practice↗

USGS2026

The influence of tree canopy cover data choices on urban ecosystem accounting

Because urban landscapes are heterogeneous, the methods and spatial resolution used to depict the land surface greatly influence the representation of urban features. Land cover products such as tree canopy cover (TCC) are particularly sensitive to the methodology and resolution used in their creation. Differences in TCC mapping have implications on the outcomes of ecosystem service (ES) models, including those underlying natural capital accounting. Here, we quantify the sensitivity of physical rainfall interception and local climate regulation ES models for 189 U.S. cities to TCC inputs from four TCC products: a) National Land Cover Database (NLCD), b) Enhanced NLCD TCC, c) aggregated city-specific composite, and d) global tree canopy height dataset. We find both city-level and aggregate differences in TCC estimates, from a 38% decrease to a 3% increase relative to an aggregated high-resolution product. These differences result in up to 3% overestimations and 27% underestimation of rainfall interception and 2–56% underestimation of local climate regulation ES. City size, population, and greenness in addition to climatic variation drove differences between TCC products, and this variation requires users to carefully consider the choice of input data for any planned analysis. Though high-resolution data can offer greater nuance and accuracy, more limited spatiotemporal availability can hinder their usefulness for long-term monitoring applications such as natural capital accounting. The differences found in this study provide valuable insights for making informed decisions on data inputs for use in urban ecosystem research and for contextualizing model outcomes.

Contiguous United States↗

USGS2026

Analyzing land characteristics associated with historical large-scale solar photovoltaic deployment in the United States

Large-scale solar (LSS) deployment has accelerated rapidly across the United States, yet comprehensive understanding of its siting patterns remains limited. Here, we present a national-scale geospatial assessment of land characteristics converted for LSS development and apply statistical analyses to evaluate whether installations are disproportionately concentrated within specific land types. We find that siting patterns are strongly correlated with high solar irradiance, underscoring the role of resource quality in shaping deployment decisions. LSS projects are disproportionately concentrated on agricultural lands and shrubland. Within agricultural areas, installations predominantly occur on croplands and are strongly associated with irrigated systems. Notably, more than 90% of projects are deployed on agricultural land with Productive, Versatile, and Resilient (PVR) index values of land quality exceeding the national median. These findings highlight the need for strategic siting frameworks that reconcile solar development with the conservation of agriculturally valuable land.

Environmental Research Letters↗

USGS2026

Leveraging socioeconomic flows to inform shared, migratory species conservation

Migratory species, and the many cultural and economic values they provide, are declining worldwide. Previous research has quantified ecosystem service flows for single migratory species to provide valuable information on the dynamics of socio-ecological systems to inform cross-jurisdictional management. There are efficiencies in implementation to be gained from considering the dynamics of multiple species (e.g., ecological guilds) simultaneously. As proof of concept, this paper demonstrates how ecosystem service flows can be aggregated spatially for a group of three North American migratory species. We further present a flexible approach to estimating how conservation funding can be allocated equitably between regions of the migratory range. Results show that most benefits from these three migratory species are supported locally by habitat within each region, but net interregional flows exist, including a $33.1M annual subsidy from Mexico to the U.S. and Canada. Results also suggest that directing 18% of net conservation funding raised for these species in the U.S. and Canada toward conservation projects in Mexico would redress inequities in shared management responsibility. Considering the values provided by multiple species simultaneously has the potential to broaden coalitions and expedite negotiation of international agreements by providing a better shared understanding of the benefits to each party.

North America↗

USGS2026

Moving toward a more human-oriented analysis of urban heat: Examining differences of heat exposure intensity at busy commuting locations

Examining urban thermal environments has become a critical area of research spanning epidemiology, urban planning, and ecology. While traditional metrics like air temperature ( T air ) and satellite-derived surface temperature dominate urban heat studies, these measures often fail to reflect how people actually experience thermal exposure intensity. More human-oriented metrics, such as mean radiant temperature (MRT), and the wet bulb globe temperature (WBGT), better capture this lived experience, particularly at locations where people are likely to encounter outdoor heat, such as bus stops. Human demographics further complicate heat exposure, as access to cooling resources like trees and greenspaces can vary by neighborhood income. Our study addresses these complications by collecting thermal data across 60 commuting locations in Denver, Colorado in the summer. We evaluate (1) the extent to which more human-oriented metrics capture thermal exposure compared to T air and LST, and (2) how heat exposure varies by neighborhood income levels. We observed that bus stops in low-income neighborhoods had an MRT increase 2.8 °C compared wealthier neighborhoods, and that income-driven differences in MRT and WBGT strongly depended on bus stop aspect. After accounting for solar orientation, differences in MRT increased to as much as 6.3 °C at north-facing stops. Our results suggest tree canopy shade explains some observed heat exposure patterns, with south facing bus stops seeing a MRT and WBGT decrease of 0.42 °C and 0.11 °C from a percent increase in tree canopy. Interestingly, depending on bus stop aspect, nearby buildings can increase MRT and WBGT (facing east), or decrease MRT and WBGT (facing south) If planners aim to address this issue, consideration of bus stops, and land covers configuration may help.

Colorado↗

USGS2026

Density dependence and habitat selection affect overwintering abundance of monarch butterflies at regional and site scales in California

The monarch butterfly ( Danaus plexippus ) is a species of iconic cultural interest. Thanks to annual overwintering monarch counts at hundreds of locations in coastal California, we are able to track fluctuations with high temporal and spatial resolution. Between 1997 and 2024, monarch populations at overwintering sites in the western United States experienced severe dips, at times (2018–2020, 2023–2024) giving the appearance of a population collapse. From 2018 to present, the Pismo State Beach Overwintering Monarch Grove has conducted multiple counts during overwintering and geolocated counts of individual monarch clusters to specific trees within the site. This study determined how annual monarch population variability is influenced by both climate and prior year population density at the state, region, and overwintering-site scale. Furthermore, through a machine-learning process, we investigated how overwintering site configuration and structure drive monarch winter space-use dynamics within the Pismo Beach site. Our approach found monarchs exhibit a preference for specific overwintering sites in California, and that 64% of annual variability of counts across sites can be explained by climate and density dependence, with density dependence explaining 50% of total variability. Within the site we found very little regional climate effect, but individual trees, tree size, distance to boundary, and the amount of shade were all strong indicators of monarch presence. Additionally, only 11 out of 320 trees at the Pismo Beach site accounted for 83.6% of all counts over 6 years, highlighting how monarchs use specific trees and how tree structure may create preferred microclimates for clustering.

California↗

USGS2026

Out with the old: Empirical trends in U.S. land-based wind turbine decommissioning and repowering

A growing number of wind turbines (WTs) across the globe are now reaching or exceeding their expected service lifetime; WT decommissioning is on the rise. Accordingly, questions pertaining to WT end-of-life have risen in importance in policy and practice. Yet, research on the various factors relating to WT decommissioning is relatively sparse. Moreover, the key assumptions underpinning that prior research (e.g., the lifespan of WTs, characteristics of WTs being decommissioned, and whether the site is repowered with new WTs) have never been empirically tested across a large set of decommissioned WTs. Leveraging a uniquely comprehensive and spatially explicit dataset of decommissioned WTs in the United States, this research analyzes spatial, technological, and temporal trends in WT decommissioning and develops a novel predictive model for WT decommissioning. Our analysis pinpoints more than 12,400 WTs that have been fully decommissioned in the United States., the majority of which have been relatively old (> 30 years) and small (< 200 kW). While a WT's age alone is a good predictor of the likelihood of decommissioning, other factors such as the size of the WT and recent performance are also important and significant predictors. Most sites where decommissioning has occurred have seen subsequent repowering, with repowered plants featuring substantially fewer WTs (−86 on average) and higher rated plant capacity (+62 MW on average). Many existing WTs in the U.S. are approaching the end of their expected life with roughly 7500 being 20 or more years old. Findings can help policymakers and stakeholders begin preparing for this potential wave of future decommissioning and repowering.

Wind Energy↗

USGS2026

Hierarchical mixture models and high-resolution monitoring data can inform siting and operational strategies to mitigate bat fatalities at wind turbines

Bats provide critical ecosystem services, but bat fatalities due to wind energy development may imperil some bat populations. Statistical models are used to estimate the total fatalities that occur based on carcasses observed during monitoring surveys. Current models often estimate fatalities aggregated across species, time, and/or turbines, but fall short of reliably informing siting and operational collision mitigation strategies that account for species-specific fatality patterns on a fine spatiotemporal scale. We developed a hierarchical mixture model for estimating species-specific covariate effects and total fatalities per species at each turbine on weekly intervals. We applied the model to a high-resolution dataset of bat carcasses found during turbine searches across nineteen wind facilities in Iowa over two years. Our model explains species-specific variation in bat fatalities at individual wind turbines according to turbine proximity to bat habitat, turbine design specifications, seasonal trends, and weather conditions such as nightly air temperature, air pressure, and wind speed. Turbines located on the edge of wind facilities had higher fatalities, and proximity to roosting and foraging habitat accounted for variation in species-specific fatality estimates. These insights into turbine placement effects can inform siting strategies. We also discovered species-specific relationships with average nightly wind speed and air temperature, among other weather conditions, that could inform operational mitigation strategies such as smart curtailment. Our model can transform observations of carcasses found during turbine searches across multiple facilities, years, and variable search efforts into estimates of total fatalities per species associated with species-specific spatial, temporal, and environmental covariate effects.

Ecological Informatics↗

USGS2025

The rise of U.S. photovoltaics: An exploration of land use density trends in large-scale solar facility attributes, 2012-2021

An energy transition is underway in the United States; renewable energy generation is now on par with coal and nuclear generation. The number of large-scale solar photovoltaic facilities increased approximately tenfold between 2012 and 2021, with an associated 25-fold increase in cumulative installed capacity. With ambitious decarbonization and renewable energy deployment goals at both the federal and state levels, deployments of large-scale solar photovoltaic facilities will continue apace. This growth is likely to be complex with ripples of impacts felt throughout different aspects of society, and thus accurate solar land use metrics allowing more accurate predictions are of value to policymakers, planners, and other stakeholders in the future photovoltaic build-out. In this paper, we leverage data from the newly released US Large-Scale Solar Photovoltaic Database to examine recent trends in large-scale solar photovoltaic land use. We analyze the relationships between solar array capacity density (W/acre) and a range of facility attributes to better understand the future land requirements of solar capacity expansion over the coming years. Installed capacity was the single strongest determinant of solar array area. However, we found substantial variation in capacity density across facility attributes, including mount type, latitude, urbanicity, time, and prior land use.

conterminous United States↗

USGS2025

An enhanced national-scale urban tree canopy cover dataset for the United States

Moderate-resolution (30-m) national map products have limited capacity to represent fine-scale, heterogeneous urban forms and processes, yet improvements from incorporating higher resolution predictor data remain rare. In this study, we applied random forest models to high-resolution land cover data for 71 U.S. urban areas, moderate-resolution National Land Cover Database (NLCD) Tree Canopy Cover (TCC), and additional explanatory climatic and structural data to develop an enhanced urban TCC dataset for U.S. urban areas. With a coefficient of determination (R 2 ) of 0.747, our model estimated TCC within 3% for 62 urban areas and added 13.4% more city-level TCC on average, compared to the native NLCD TCC product. Cross validations indicated model stability suitable for building a national-scale TCC dataset (median R 2 of 0.752, 0.675, and 0.743 for 1,000-fold cross validation, urban area leave-one-out cross validation, and cross validation by Census block group median year built, respectively). Additionally, our model code can be used to improve moderate-resolution TCC in other parts of the world where high-resolution land cover data have limited spatiotemporal availability.

conterminous United States↗

USGS2025

A tiered assessment framework for interregional flows of ecosystem services from migratory species

The Intergovernmental Science–Policy Platform on Biodiversity and Ecosystem Services has called for assessments explicitly accounting for interregional flows of ecosystem services (ESs) across geographic scales. An important type of interregional ES flow is generated by the long-distance movements of migratory species. Many migratory species provide important benefits to people, and due to migration dynamics, ESs provided in one location may be affected by habitat conservation, or lack thereof, in other locations. The state of the science on interregional flows of ESs from migratory species, however, is nascent and lacks structure needed to consistently characterize flows. We developed a 4-tiered system for categorizing assessments and the conclusions they can support based on 4 levels of ecological and socioeconomic information, ranging from incomplete to high, and how they are combined. The 4 tiers of assessment are based on differing levels of detail in the estimation of system-level ecological and socioeconomic information on a species and the services it provides: telecoupled ESs, qualitative flows, quantitative static flows, and quantitative dynamic flows. Recent assessment studies largely fall within the first tier, which does not quantify flows. Socioeconomic and ecological information are needed to achieve each tier. Our framework can be used to identify and classify a range of methods, with varying time and data requirements, that can be used to maximize the information content and relevance of ES assessments for migratory species based on available resources.

Conservation Biology↗

USGS2025

Land-use and socioeconomic time-series reveal legacy of redlining on present-day gentrification within a growing United States city

Home Owners’ Loan Corporation (HOLC) maps illustrated patterns of segregation in United States cites in the 1930s. As the causes and drivers of demographic and land-use segregation vary over years, these maps provide an important spatial lens in determining how patterns of segregation spatially and temporally developed during the past century. Using a high-resolution land-use time series (1937-2018) of Denver, Colorado, USA, in conjunction with 80 years of U.S. Census data, we found divergent land-use and demographics patterns across HOLC categories were both pre-existent to the establishment of HOLC mapping and continued to develop over time. Over this period, areas deemed “declining” or “hazardous” had more diverse land use compared to “desirable” areas. “Desirable” areas were dominated by one land-use type (single-family residential), while single-family residential diminished in prominence in the “declining/hazardous” areas. This divergence became more established decades after HOLC mapping, with impact to racial metrics and low-income households. We found changes in these demographic patterns also occurred between 2000 and 2019, highlighting how processes like gentrification can develop from both rapid demographic and land-use changes. This study demonstrates how the legacy of urban segregation develops over decades and can simultaneously persist in some neighborhoods while providing openings for fast-paced gentrification in others.

Colorado↗

USGS2024

Potential for spatial coexistence of a transboundary migratory species and wind energy development

Global expansion in wind energy development is a notable achievement of the international community’s effort to reduce carbon emissions during energy production. However, the increasing number of wind turbines have unintended consequences for migratory birds and bats. Wind turbine curtailment and other mitigation strategies can reduce fatalities, but improved spatial and temporal data are needed to identify the most effective way for wind energy development and volant migratory species to coexist. Mexican free-tailed bats ( Tadarida brasiliensis mexicana ) account for a large proportion of known bat fatalities at wind facilities in the southwestern US. We examined the geographic concordance between existing wind energy generation facilities, areas of high wind potential amenable for future deployment of wind facilities, and seasonally suitable habitat for these bats. We used ecological niche modeling to determine species distribution during each of 4 seasons. We used a multi-criteria GIS-based approach to produce a wind turbine siting suitability map. We identified seasonal locations with highest and lowest potential for the species’ probability of occurrence, providing a potential explanation for the higher observed fatalities during fall migration. Thirty percent of 33,606 wind turbines within the southwestern US occurred in highly suitable areas for Mexican free-tailed bats, primarily in west Texas. There is also broad spatial overlap between areas of high wind potential and areas of suitable habitat for Mexican free-tailed bats. Because of this high degree of overlap, our results indicate that post-construction strategies, such as curtailing the timing of operations and deterrents, would be more effective for bat conservation than strategic siting of new wind energy installations.

Scientific Reports↗

USGS2024

Challenges creating monarch butterfly management strategies for electric power companies in the United States

Returning monarch butterflies ( Danaus plexippus ) to sustainable levels of abundance will require an array of contributors to protect and restore habitat over broad areas. Due to the diversity and scale of land managed by electric power companies across the monarch range, plus an additional 32 million hectares needed for new solar arrays by 2050 to meet renewable energy goals, the industry may have potential to contribute to monarch conservation. However, it is challenging to clearly understand an individual company’s potential for monarch conservation because of the scale and distribution of their specific land assets (ranging from 4,800 to 240,000 hectares in this study alone), the complexity of monarch science, and the lack of a science-based approach for evaluating large land assets for monarch habitat. With monarchs potentially being protected under the United States Endangered Species Act in the future and thereby limiting land management approaches, there is interest from electric power companies to understand how their lands relate to monarchs. In collaboration with companies, we developed a GIS-based model to identify company landholdings that contain high-quality monarch habitat and applied the model to specific landholdings of eight power companies in the United States. We then facilitated discussions with company teams to balance conservation goals, corporate risk, and social opinion. This paper describes non-confidential results for developing a national GIS-based monarch habitat model and applying it to electric power companies who are considering monarch conservation while simultaneously transitioning to a new clean energy future. The model and applied experience may be useful for other organizations working across large landscapes to manage monarchs.

conterminous United States↗

USGS2024

Changes in landscape and climate in Mexico and Texas reveal small effects on migratory habitat of monarch butterflies (Danaus plexippus)

The decline of the iconic monarch butterfly ( Danaus plexippus ) in North America has motivated research on the impacts of land use and land cover (LULC) change and climate variability on monarch habitat and population dynamics. We investigated spring and fall trends in LULC, milkweed and nectar resources over a 20-year period, and ~ 30 years of climate variables in Mexico and Texas, U.S. This region supports spring breeding, and spring and fall migration during the annual life cycle of the monarch. We estimated a − 2.9% decline in milkweed in Texas, but little to no change in Mexico. Fall and spring nectar resources declined < 1% in both study extents. Vegetation greenness increased in the fall and spring in Mexico while the other climate variables did not change in both Mexico and Texas. Monarch habitat in Mexico and Texas appears relatively more intact than in the midwestern, agricultural landscapes of the U.S. Given the relatively modest observed changes in nectar and milkweed, the relatively stable climate conditions, and increased vegetation greenness in Mexico, it seems unlikely that habitat loss (quantity or quality) in Mexico and Texas has caused large declines in population size or survival during migration.

Scientific Reports↗

USGS2024

The geographic extent of bird populations affected by renewable-energy development

Bird populations are declining globally. Wind and solar energy can reduce emissions of fossil fuels that drive anthropogenic climate change, yet renewable-energy production represents a potential threat to bird species. Surveys to assess potential effects at renewable-energy facilities are exclusively local, and the geographic extent encompassed by birds killed at these facilities is largely unknown, which creates challenges for minimizing and mitigating the population-level and cumulative effects of these fatalities. We performed geospatial analyses of stable hydrogen isotope data obtained from feathers of 871 individuals of 24 bird species found dead at solar- and wind-energy facilities in California (USA). Most species had individuals with a mix of origins, ranging from 23% to 98% nonlocal. Mean minimum distances to areas of likely origin for nonlocal individuals were as close as 97 to >1250 km, and these minimum distances were larger for species found at solar-energy facilities in deserts than at wind-energy facilities in grasslands (Cohen's d = 6.5). Fatalities were drawn from an estimated 30–100% of species’ desingated ranges, and this percentage was significantly smaller for species with large ranges found at wind facilities (Pearson's r = −0.67). Temporal patterns in the geographic origin of fatalities suggested that migratory movements and nonmigratory movements, such as dispersal and nomadism, influence exposure to fatality risk for these birds. Our results illustrate the power of using stable isotope data to assess the geographic extent of renewable-energy fatalities on birds. As the buildout of renewable-energy facilities continues, accurate assessment of the geographic footprint of wildlife fatalities can be used to inform compensatory mitigation for their population-level and cumulative effects.

Conservation Biology↗