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USGS2025

Using long-term ecological datasets to unravel the impacts of short-term meteorological disturbances on phytoplankton communities

Extreme meteorological events such as storms are increasing in frequency and intensity, but our knowledge of their impacts on aquatic ecosystems and emergent system properties is limited. Understanding the ecological impacts of storms on the dynamics of primary producers remains a challenge that needs to be addressed to assess the vulnerability of freshwater ecosystems to extreme weather conditions and climate change. One promising approach to gain insights into storm impacts on phytoplankton community dynamics is to analyse long-term monitoring datasets. However, such an approach requires disentangling the impacts of short-term meteorological disturbances from the effects of the seasonal trajectories of meteorological conditions. To this end, we applied boosted regression tree models to phytoplankton time series from eight relatively large lakes on four continents, coupled with a procedure adapted to detect and quantify rare events. Overall, the patterns and potential drivers we identified provide important insights into the responses of lakes to short-term meteorological events and highlight differences in the response of phytoplankton communities according to lake morphological characteristics. Our results indicated that deepened thermoclines and lake-specific combinations of drivers describing altered thermal structures caused deviations from the typical trajectories of seasonal phytoplankton succession. For shallow polymictic lakes, shifts in phytoplankton succession also depended on changes in light availability. Overall, our study highlights the value of long-term monitoring to improve our understanding of phytoplankton sensitivity to short-term meteorological disturbances.

Freshwater Biology↗

USGS2021

Vulnerability assessment and adaptation planning for projected changes in water quality and quantity for protected areas in the upper Midwest

Climate change and the extreme weather associated with it can be a major challenge to natural resource managers charged with the protection, restoration, recovery, and management of wetlands and wildlife habitats. Forecasting the potential impacts of climate changes will be important for decision-makers and land managers seeking to minimize impacts to habitats, infrastructure, and wildlife populations and prepare for the future. In collaboration with U.S. Fish and Wildlife Service (FWS) managers, we developed a climate change vulnerability assessment to spatially evaluate climate vulnerabilities across the Midwest region. To create the vulnerability assessment, we convened resource managers and scientists working across the region to determine the components and scope of the vulnerability assessment. The vulnerability assessment was watershed-based and composed of 15 indicators of climate change and five indicators that reflect the capacity of a watershed to buffer against the effects of climate change. The indicators were selected by FWS managers to have broad applicability across systems and programs in the FWS. To facilitate usability, we created an online application that allows users to generate customizable vulnerability assessments. We then integrated the assessment into a process for engaging in climate change adaptation thinking as a precursor to formal planning, implementation, and monitoring of adaptation actions. The process we designed focused on understanding the components of the system, assessing climate change vulnerabilities, creating and describing possible climate change scenarios, and identifying impacts and adaptation options for each scenario. We piloted this process in a virtual workshop setting with FWS managers and biologists on the topic of managed wetland systems. This work is currently being used by the FWS to better understand regional vulnerabilities and adaptation strategies and to advance integration of climate science into formal planning processes.

Illinois, Indiana, Iowa, Michigan, Minnesota, Miss↗

USGS2019

Ecological consequences of anomalies in atmospheric moisture and snowpack

Although increased frequency of extreme‐weather events is one of the most secure predictions associated with contemporary climate change, effects of such events on distribution and abundance of climate‐sensitive species remain poorly understood. Montane ecosystems may be especially sensitive to extreme weather because of complex abiotic and biotic interactions that propagate from climate‐driven reductions in snowpack. Snowpack not only protects subnivean biotas from extreme cold, but also influences forage availability through timing of melt‐off and water availability. We related relative abundances of an alpine mammal, the American pika ( Ochotona princeps ), to measures of weather and snowpack dynamics over an 8‐yr period that included before and after a year of record‐low snowpack in Washington, USA. We sought to (1) quantify any change in pika abundance associated with the snowpack anomaly and (2) identify aspects of weather and snowpack that influenced abundance of pikas. Pikas showed a 1‐yr lag response to the snowpack anomaly and exhibited marked declines in abundance at elevations below 1,400 m simultaneous with increased abundances at higher elevations. Atmospheric moisture, indexed by vapor pressure deficit (VPD), was especially important, evidenced by strong support for the top‐ranked model that included the interaction of VPD with snowpack duration. Notably, our novel application of VPD from gridded climate data for analyses of animal abundances shows strong potential for improving species distribution models because VPD represents an important aspect of weather that influences the physiology and habitat of biota. Pikas were apparently affected by cold stress without snowpack at mid elevations, whereas changes to forage associated with snowpack and VPD were influential at high and low elevations. Our results reveal context dependency in pika responses to weather and illustrate how snow drought can lead to rapid change in the abundance of subnivean animals.

Washington↗

USGS2021

A typology of drought decision making: Synthesizing across cases to understand drought preparedness and response actions

Drought is an inescapable reality in many regions, including much of the western United States. With climate change, droughts are predicted to intensify and occur more frequently, making the imperative for drought management even greater. Many diverse actors – including private landowners, business owners, scientists, non-governmental organizations (NGOs), and managers and policymakers within tribal, local, state, and federal government agencies – play multiple, often overlapping roles in preparing for and responding to drought. Managing water is, of course, one of the most important roles that humans play in both mitigating and responding to droughts; but, focusing only on “water managers” or “water management” fails to capture key elements related to the broader category of drought management. The respective roles played by those managing drought (as distinct from water managers), the interactions among them, and the consequences in particular contexts, are not well understood. Our team synthesized insights from 10 in-depth case studies to understand key facets of decision making about drought preparedness and response. We present a typology with four elements that collectively describe how decisions about drought preparedness and response are made (context and objective for a decision; actors responsible; choice being made or action taken; and how decisions interact with and influence other decisions). The typology provides a framework for system-level understanding of how and by whom complex decisions about drought management are made. Greater system-level understanding helps decision makers, program and research funders, and scientists to identify constraints to and opportunities for action, to learn from the past, and to integrate ecological impacts, thereby facilitating social learning among diverse participants in drought preparedness and response.

Colordao, Idaho, Montana, New Mexico, Oklahoma, Or↗

USGS2024

ENSO-based outlook of droughts and agricultural outcomes in Afghanistan

Drought is one of the key drivers of food insecurity in Afghanistan, which is among the most food insecure countries in the world. In this study, we build on previous research and seek to answer the central question: “What is the influence of El Niño-Southern Oscillation (ENSO) on drought outlooks and agricultural yield outcome in Afghanistan, and how do these influences vary spatially ?” We do so by utilizing multiple indicators of droughts and available wheat yield reports. We find a clear distinction in the probability of drought (defined as being in the lower tercile) in Afghanistan during La Niña compared to El Niño events since 1981. The probability of drought in Afghanistan increased during La Niña, particularly in the North, Northeast, and West regions. La Niña events are related to an increase in the probability of snow drought, particularly in parts of the Amu Darya basin. It is found that relative to El Niño events, snow water equivalent [total runoff] during La Niña events January–March (March–July total runoff) decreases between 9% and 30% (28%–42%) for the five major basins in the country. The probability of agricultural drought during La Niña events is found to be higher than 70% in the rainfed and irrigated areas of the Northeast, North, and West regions. This result is at least partly supported by reported wheat yield composites related to La Niña events that tend to be lower than for El Niño events across all regions in the case of rainfed wheat (statistically significant in Northeast, West, and South regions) and in some cases for irrigated wheat. The results of this study have direct implications for improving early warning of worsening food insecurity in Afghanistan during La Niña events, given that we now have long-lead and skillful forecasts of ENSO up to 18–24 months in advance, which could potentially be used to provide earlier warning of worsening food insecurity in Afghanistan

Weather and Climate Extremes↗

USGS2021

Oregon and Landsat

Oregon’s landscape is as complex and diverse as it is beautiful. Mountain peaks in the Cascade Range soar higher than 10,000 feet. Crater Lake sinks to a depth of 1,943 feet, making it the deepest lake in the United States. Oregon’s lands feature forests, farm fields, grasslands, ocean coastline, rivers, a semidesert, and mountain ranges that stretch across the State. A wide range of birds, animals, and fish—including 16 federally endangered species—share this space with more than 4 million people. With Oregon’s economy tied to these natural resources, industries like agriculture, timber, and fishing interlace with the well-being of wildlife and residents. Landsat data and imagery are one of many U.S. Geological Survey tools used by State resource managers and scientists to help achieve a natural balance and provide information about forests, habitats, and much more to Oregon decision makers. This will become even more important as research indicates climate change will make extreme weather more likely, leading to the likely increase in droughts, infestation, wildfires, and other natural hazards.

Oregon↗

USGS2021

Arizona and Landsat

Arizona is a land of massive grandeur, deep gorges, lofty mountains, immense plains, and elevated mesas—and, without question, its crown jewel is the Grand Canyon. The spectacular canyon, one of the seven natural wonders of the world, was created when the Colorado River carved a channel through northern Arizona, revealing nearly two billion years of the Earth's history. Yet, for all its ancient beauty, Arizona and its landscapes are experiencing a transformation. Arizonans face more extreme temperatures and drought because of climate change. Amid a drought in the western United States, Lake Mead, one of Arizona's main water resources, dropped to a record low level in June 2021. Climate change is making extreme weather events such as dust storms and heat waves more common, posing higher risks to human health, according to the Centers for Disease Control and Prevention.

Arizona↗

USGS2016

Evaluation of downscaled, gridded climate data for the conterminous United States

Weather and climate affect many ecological processes, making spatially continuous yet fine-resolution weather data desirable for ecological research and predictions. Numerous downscaled weather data sets exist, but little attempt has been made to evaluate them systematically. Here we address this shortcoming by focusing on four major questions: (1) How accurate are downscaled, gridded climate data sets in terms of temperature and precipitation estimates?, (2) Are there significant regional differences in accuracy among data sets?, (3) How accurate are their mean values compared with extremes?, and (4) Does their accuracy depend on spatial resolution? We compared eight widely used downscaled data sets that provide gridded daily weather data for recent decades across the United States. We found considerable differences among data sets and between downscaled and weather station data. Temperature is represented more accurately than precipitation, and climate averages are more accurate than weather extremes. The data set exhibiting the best agreement with station data varies among ecoregions. Surprisingly, the accuracy of the data sets does not depend on spatial resolution. Although some inherent differences among data sets and weather station data are to be expected, our findings highlight how much different interpolation methods affect downscaled weather data, even for local comparisons with nearby weather stations located inside a grid cell. More broadly, our results highlight the need for careful consideration among different available data sets in terms of which variables they describe best, where they perform best, and their resolution, when selecting a downscaled weather data set for a given ecological application.

Ecological Applications↗

USGS2026

Climate-driven shifts in snowpack conditions favorable for wet snow avalanches: Insights from snow cover model simulations

Forecasting wet snow avalanches remains a major challenge due to their temporal and spatial variability. Long-term climate trends are producing more variable and extreme weather, creating conditions outside historical experience, and increasing forecasting uncertainties. To assess how climate change affects the frequency and timing of wet snow avalanches, we examined the long-term conditions that support wet snow formation. Specifically, we ask: Will the onset of wet snow avalanche conditions or season end shift toward the mid century? And will maximum snow height decrease in avalanche starting zones? To address these questions, we analyze long-term snow cover simulations across our study site in Glacier National Park, Montana, located in an intermountain snow climate. We examined trends in simulated snow depth, and timing of liquid water infiltration over the past four decades (1979–2023) using a physically based snow cover model. To force the model with meteorological data, we use the long-term regional hydroclimate reanalysis dataset U.S. Geological Survey CONUS404 with 4 km spatial resolution and 1h temporal resolution. The use of gridded meteorological inputs to drive a one-dimensional point model introduces inherent scale mismatches. To address this limitation, we use multiple grid points within the study area to simulate a more representative, generalized snowpack, and filter the grid points based on elevation to distinguish between upper- and mid-elevation starting zones. Finally, we analyzed shifts in snow depth, melt-out-day, and LWCindex (bulk liquid water content (LWC) normalized by the residual water content). We use snow depth as a proxy for changes in slab thickness, the LWCindexas an indicator of wet snow avalanche conditions, and melt-out date as a measure of shifts in season length. We ran simulations on flat terrain and on north- and south-facing virtual slopes (38°), across mid-elevation (1,600–1,900 m) and upper-elevation (≥1,900 m) sites for the historical dataset as baseline and a Pseudo-Global-Warming (PGW) dataset to identify a warming driven shift. Across all aspects and both elevation bands, PGW forcing produces a consistent reduction in annual maximum snow depth (median shift −0.15 to −0.26 m, p<0.001) over 44 seasons, with the largest reductions on north-facing slopes and a modest but significant strengthening of this reduction over the 44-year simulated record. Melt-out starts 10–14 days earlier under PGW across all aspect–elevation combinations (p<0.001), again most pronounced on north-facing, higher-elevation terrain. The LWCindex threshold-crossing dates likewise shift earlier under PGW, indicating an earlier onset of wet snow avalanche conditions across the domain. Together, these results point to a snowpack that is both thinner and wetter earlier in the season under future warming, with the strongest signal consistently on north-facing slopes at higher elevation. This work lays the groundwork for climate-informed forecasting and mitigation and offers historical context for avalanche operations in a changing climate. Understanding long-term trends can help avalanche professionals interpret current observations, improve wet snow avalanche forecasting, and develop more effective mitigation strategies in a warming climate.

Montana↗

USGS2026

Mass mortality of avian migrants in New Mexico, USA, that coincided with an extreme weather event

Many birds are migratory, and this life history strategy allows for maximized access to seasonally abundant resources and favorable climates. However, migration exposes birds to threats and stressors, resulting in high mortality during migration. Anthropogenic landscape alterations and climate change have intensified threats, and mass mortality events linked to extreme weather are more common in recent decades. Documenting mass mortality is critical for predicting future occurrences and implementing effective conservation. Here, we describe a mortality event that occurred throughout New Mexico, USA in fall 2020. Carcasses began appearing in the region in mid-August, during a period of extreme heat and drought. Following an extreme cold weather event on September 8–9 th , the number of carcasses increased dramatically and expanded throughout the state. In total, we collected 628 carcasses comprising 58 species within Doña Ana and Otero Counties in New Mexico. Necropsy determined emaciation was the cause of death for 74.6% of carcasses. Live birds captured during the period of peak mortality (n = 223) were in similarly poor condition. This event provides a striking example of how multiple types of extreme stressors, in this case widespread drought and unseasonal cold, coincided with a mortality event, indicating a possible synergistic relationship between these factors and the mass mortality. Mortality events are likely to increase in frequency with intensifying climate change. Establishment of networks of biologists and researchers could improve our ability to identify and communicate developing mortality events, organize data collection, and improve understanding of the causes and consequences of mortality.

New Mexico↗

USGS2025

2024 Surprise Inlet landslides: Insights from a prototype landslide‐triggered tsunami monitoring system in Prince William Sound, Alaska

Alaska's coastal communities face growing landslide hazards owing to glacier retreat and extreme weather intensified by the warming climate, yet hazard monitoring remains challenging. As part of ongoing experimental monitoring in Prince William Sound, we detected three large landslides (0.5–2.3 M m 3 ) at Surprise Inlet on 20 September 2024, within the span of an hour. These events were identified in near real-time through seismic data and later confirmed using satellite imagery, tidal records, and infrasound. The landslides generated a modest tsunami, and a 4 cm wave was recorded by a tide gauge 18 km away, marking the first recorded landslide to reach water since monitoring began in this region in 2021. Here, we examine the detection and interpretation of these landslides using multiple data sources and modeling. We demonstrate the effectiveness of this regional seismic monitoring system and show how complementary instrumentation, where available, can enhance detection capabilities.

Alaska↗

USGS2019

Evidence of an extreme weather‐induced phenological mismatch and a local extirpation of the endangered Karner blue butterfly

In 2011, an experiment was undertaken to examine spring synchrony between the endangered Karner blue butterfly ( Lycaeides melissa samuelis ) (Kbb) and its obligate host plant, wild blue lupine ( Lupinus perennis ) at Indiana Dunes National Lakeshore (INDU), where the southernmost population of Kbb occurred at the time of this study. From 2012 to 2014, field‐placed Kbb eggs were observed for larvae hatching in conjunction with observations of lupine emergence in oak savanna habitat. In 2012, 61% of Kbb hatched when <5% of lupine had emerged due to an extreme early spring event as compared to subsequent years where temporal overlap was >15% between Kbb and lupine. Laboratory experiments testing the sensitivity of Kbb hatching to warm temperatures during the winter of 2011–2012 confirmed that Kbb eggs were susceptible to temperature‐induced hatching. In the summer of 2012, second generation Kbb larvae feeding on sun‐exposed lupine had higher mortality due to the heat and drought conditions that resulted in earlier plant senescence. Following 2012, Kbb were no longer observed at INDU. This observation illustrates the pressing need for adaptive management strategies that account for extreme weather events brought on by climate change.

Indiana↗

USGS2022

Alabama and Landsat

Alabama’s warm climate and rich soil bolster its agriculture and timber industries, but they also offer ideal conditions for natural playgrounds, enjoyed by humans and the wildlife that call the open green spaces home. Alabama has 21 State parks and 11 national parks, monuments, and trails across its diverse geography. Cotton is no longer king in the Cotton State, but it remains a part of the fabric of its multibillion-dollar agriculture sector. The State also produces poultry, cattle, calves, corn, lumber, soybeans, and catfish. The State is home to Dauphin Island, the first land mass seen by migratory birds and pollinators upon their return from South America. Dauphin Island acts as a landing zone for hundreds of species, including sandpipers, plovers, and herons, and protects Alabama’s coastline. Since 1961, Dauphin Island has been the home of the Audubon Bird Sanctuary. The varied landscapes of the Cotton State face challenges from climate change, land change, and extreme weather. Satellite imagery from the U.S. Geological Survey Landsat Program can offer insight and understanding in these and other areas. Here are some ways Landsat benefits Alabama.

Alabama↗

USGS2022

Florida and Landsat

More than 21 million people call Florida home, but many more visit the peninsula each year—including a record 131 million in 2019. Residents and tourists enjoy the State’s warm weather and varied attractions amid incredibly diverse biological and natural resources. Numerous lakes and rivers, and 8,400 miles of ocean shoreline, play a prominent role, as do unique habitats like the Everglades, which are home to protected species such as the Florida manatee ( Trichechus manatus latirostris ), American crocodile ( Crocodylus acutus ), and Florida panther ( Puma concolor couguar ). The State also supports cattle, sugarcane, and citrus production—along with nearly one-half of the tree species in the United States. A changing climate is expected to bring rising sea levels and more extreme weather events. In a State where the average elevation is 100 feet above sea level, climate change could affect everything from urban shores and beaches to agriculture and forests. In addition, as cities grow, more land cover tends to shift from natural vegetation to impervious surfaces such as pavement, which can add to environmental risks such as flooding. Landsat can help Florida’s agencies, organizations, and residents monitor the State’s fragile landscapes and plan for a resilient future. Here are just a few examples of how Landsat benefits Florida.

Florida↗

USGS2020

Possible effects of climate change on ixodid ticks and the pathogens they transmit: Predictions and observations

The global climate has been changing over the last century due to greenhouse gas emissions and will continue to change over this century, accelerating without effective global efforts to reduce emissions. Ticks and tick-borne diseases (TTBDs) are inherently climate-sensitive due to the sensitivity of tick lifecycles to climate. Key direct climate and weather sensitivities include survival of individual ticks, and the duration of development and host-seeking activity of ticks. These sensitivities mean that in some regions a warming climate may increase tick survival, shorten life-cycles and lengthen the duration of tick activity seasons. Indirect effects of climate change on host communities may, with changes in tick abundance, facilitate enhanced transmission of tick-borne pathogens. High temperatures, and extreme weather events (heat, cold, and flooding) are anticipated with climate change, and these may reduce tick survival and pathogen transmission in some locations. Studies of the possible effects of climate change on TTBDs to date generally project poleward range expansion of geographical ranges (with possible contraction of ranges away from the increasingly hot tropics), upslope elevational range spread in mountainous regions, and increased abundance of ticks in many current endemic regions. However, relatively few studies, using long-term (multi-decade) observations, provide evidence of recent range changes of tick populations that could be attributed to recent climate change. Further integrated ‘One Health’ observational and modeling studies are needed to detect changes in TTBD occurrence, attribute them to climate change, and to develop predictive models of public- and animal-health needs to plan for TTBD emergence.

Journal of Medical Entomology↗

USGS2015

Implications of climate and land use change

This chapter relates ecosystem services to climate change and land use. The bulk of the chapter focuses on ecosystem services and steepland land use in the humid Neotropics – what is lost with land-cover changed, and what is gained with various types of restoration that are sustainable given private ownership. Many case studies are presented later in the white paper. The USGS contribution relates to climate change and the role of extreme weather events in land-use planning.

Book chapter↗

USGS2023

Integrating remote sensing with ground-based observations to quantify the effects of an extreme freeze event on black mangroves (Avicennia germinans) at the landscape scale

Climate change is altering the frequency and intensity of extreme weather events. Quantifying ecosystem responses to extreme events at the landscape scale is critical for understanding and responding to climate-driven change but is constrained by limited data availability. Here, we integrated remote sensing with ground-based observations to quantify landscape-scale vegetation damage from an extreme climatic event. We used ground- and satellite-based black mangrove ( Avicennia germinans ) leaf damage data from the northern Gulf of Mexico (USA and Mexico) to examine the effects of an extreme freeze in a region where black mangroves are expanding their range. The February 2021 event produced coastal temperatures as low as − 10 °C in some areas, exceeding thresholds for A. germinans damage and mortality. We used Sentinel-2 surface reflectance data to assess vegetation greenness before and after the freeze, along with ground-based observations of A. germinans leaf damage. Our results show a negative, nonlinear threshold relationship between A. germinans leaf damage and minimum temperature, with a temperature threshold for leaf damage near − 6 °C. Satellite-based analyses indicate that, at the landscape scale, damage was particularly severe along the central Texas coast, where the freeze event affected > 2000 ha of A. germinans -dominated coastal wetlands. Our analyses highlight the value of pairing remotely sensed data with regional, ground-based observations for quantifying and extrapolating the effects of extreme freeze events on mangroves and other tropical, cold-sensitive plants. The results also demonstrate how extreme freeze events govern the expansion and contraction of mangroves near northern range limits in North America.

Gulf of Mexico↗

USGS2020

Potential changes to the biology and challenges to the management of invasive sea lamprey Petromyzon marinus in the Laurentian Great Lakes due to climate change

Control programs are implemented to mitigate the damage caused by invasive species worldwide. In the highly invaded Great Lakes, the climate is expected to become warmer with more extreme weather and variable precipitation, resulting in shorter iced‐over periods and variable tributary flows as well as changes to pH and river hydrology and hydrogeomorphology. We review how climate change influences physiology, behavior, and demography of a damaging invasive species, sea lamprey ( Petromyzon marinus ), in the Great Lakes, and the consequences for sea lamprey control efforts. Sea lamprey control relies on surveys to monitor abundance of larval sea lamprey in Great Lakes tributaries. The abundance of parasitic, juvenile sea lampreys in the lakes is calculated by surveying wounding rates on lake trout ( Salvelinus namaycush ), and trap surveys are used to enumerate adult spawning runs. Chemical control using lampricides (i.e., lamprey pesticides) to target larval sea lamprey and barriers to prevent adult lamprey from reaching spawning grounds are the most important tools used for sea lamprey population control. We describe how climate change could affect larval survival in rivers, growth and maturation in lakes, phenology and the spawning migration as adults return to rivers, and the overall abundance and distribution of sea lamprey in the Great Lakes. Our review suggests that Great Lakes sea lamprey may benefit from climate change with longer growing seasons, more rapid growth, and greater access to spawning habitat, but uncertainties remain about the future availability and suitability of larval habitats. Consideration of the biology of invasive species and adaptation of the timing, intensity, and frequency of control efforts is critical to the management of biological invasions in a changing world, such as sea lamprey in the Great Lakes.

Great Lakes↗