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At least 1,693 records · Page 94Linked to original sources
USGS2026

An energetic tradeoff best explains parturition timing in grizzly bears

Timing of grizzly bear ( Ursus arctos ) parturition during hibernation has been explained by ancestral traits (delayed implantation, altricial young, obligate maternal denning), but the ultimate driver underlying precise timing has not been fully explored. Capitalizing on an observed latitudinal increase in denning duration among four populations in interior North America, we tested two alternative hypotheses. First, that birth timing results from a physiological cue that synchronizes implantation with the onset of hibernation, allowing females to forgo reproduction should they lack adequate fat stores. Alternatively, that parturition is optimally timed relative to den exit to balance an energetic tradeoff between minimizing lactation time to protect the mother and maximizing developmental time to increase cub survival. Using parturition dates previously predicted from accelerometer data (27 Dec–28 Feb), we classified 115 females according to apparent litter survival when first visually observed after den exit: 57% successful (with cubs), 22% unsuccessful (alone), and 21% unknown (not observed). The number of days between birth and den exit showed no association with latitude ( p = 0.29). It averaged 103 days among successful females but only 77 days among unsuccessful females ( p < 0.001) owing to later births and earlier exit. With each increasing degree of latitude, birth date increased by 1.0 and number of days between den entry and birth increased by 2.5 ( p < 0.001). Implantation dates were not centered on den entry dates ( p < 0.001). These results supported the energetic tradeoff hypothesis and suggested natural selection has favored a consistent number of days between parturition and den exit under average body conditions and shifts toward later or earlier births for females with lower or higher levels of bodily stored energy, respectively. This flexible tradeoff may support resilience to climate change and present a possible mechanism explaining reduced natality and cub survival in high-density populations.

Alaska, British Columbia, Idaho, Montana, Wyoming↗
USGS2026

Using demographic estimation and power analysis to inform monitoring efforts and detect declines in freshwater mussels

Population assessments can be used to determine species' viability and inform conservation efforts; however, obtaining sufficient data quality and quantity can be challenging when monitoring resources are scarce. Brook Floater ( Alasmidonta varicosa ) is a freshwater mussel that is state listed in the United States as endangered or threatened in 10 of the 14 states it occupies. Despite the conservation concern, little is known about the size and demographics of most Brook Floater populations. The primary objective of this study was to determine demographic parameters (abundance and survival) for Brook Floater at five newly established, long-term monitoring sites in Maine and Massachusetts, United States. A secondary objective was to evaluate tradeoffs of potential future sampling strategies by state natural resource agencies at these monitoring sites. Mussels were sampled at each site using visual and tactile snorkel surveys twice each summer during 2018–2020 and marked with alphanumeric tags to distinguish individuals. We considered a candidate set of capture-recapture models that allowed parameters to vary depending on year, sampling occasion, and individual shell length. Abundance estimates among sites varied widely, from 29 individuals (range: 12–119) in the Nissitissit River in Massachusetts to 311 individuals (range: 307–320) in the East Branch of the Pleasant River in Maine. Annual survival was high across all sites (0.87–0.96). Given the differences in capture probability and abundance between states, we determined the statistical power available to detect given population declines in Massachusetts and explored alternative population abundance estimators in Maine. The power analysis suggested that the existing sampling regimen in Maine is likely adequate while sampling in Massachusetts may require additional occasions each year to realistically detect population declines with sufficient statistical power. This analysis demonstrates the utility of considering sampling frequency when designing capture-recapture studies for freshwater mussels and other taxa.

Maine, Massachusetts↗
USGS2026

A 2.5 km movement by a potentially ill white-tailed deer along Nantasket Beach in suburban Massachusetts, USA

White-tailed deer ( Odocoileus virginianus ) ecology has received significant research attention, yet there is a need for further synthetic work on the species across environmental contexts and research areas. Opportunistic natural history accounts can help identify new conceptual links and research directions by offering new observations and ideas, synthesizing context from the literature, and highlighting gaps in understanding. We provide an opportunistic account of a 2.5 km movement of a white-tailed deer walking, wading, and swimming along Nantasket Beach in a suburban context in Massachusetts, USA. The deer displayed behaviors that could potentially be reflective of trauma, disorientation, or illness, including possibly symptomatic head movements and crouching behavior. The behavior of the deer may also have been influenced by the coastal and suburban context in which the observation took place. Our account explores swimming, deer behavior, and possible illness in a coastal, suburban context. We highlight the need for additional research on the ecology and management of white-tailed deer, including swimming and disease in coastal, marine, and developed contexts, and intersections across these areas.

Massachusetts↗
USGS2026

Disease, drought, and warming: A triple threat to a declining high-elevation amphibian

Managing species in an uncertain future is a reality for natural resource decision makers. Climate change is expected to exacerbate threats such as habitat loss and disease, and cause phenological mismatches, but there is uncertainty in the magnitude of these effects. Amphibians are among the most threatened taxa on earth, and most species in North America are uniquely tied to water availability for breeding, larval development, thermal refugia, and food availability. Changes in water availability and temperature may result in phenological mismatches with one or more of these processes. Thus, quantifying the dependency of amphibians to water on the landscape is critical to understanding how species may respond, as well as understanding the interplay with other threats, such as disease. We developed a dynamic co-occurrence occupancy model to explore the effects of climate change on the breeding occurrence of boreal toads ( Anaxyrus boreas ) and the amphibian chytrid fungus ( Batrachochytrium dendrobatidis , Bd) in the southern Rocky Mountains (SRM). We derived novel covariates to test hypotheses related to multi-generational impacts of climate on the dynamics of both boreal toad breeding and Bd. We report estimates of current (2001–2019) and future (2055–2069) occupancy under a range of plausible climate scenarios. The probability of boreal toad breeding occurrence at a site in the SRM declined > 40% from 2001 to 2019, and further declines are likely under future scenarios, particularly as active season length increases. To help integrate this information into management, we developed a web-based decision support tool to summarize predicted future hydrological and occupancy conditions.

Colorado, New Mexico, Wyoming↗
USGS2021

Resilience of terrestrial and aquatic fauna to historical and future wildfire regimes in western North America

Wildfires in many western North American forests are becoming more frequent, larger, and severe, with changed seasonal patterns. In response, coniferous forest ecosystems will transition toward dominance by fire-adapted hardwoods, shrubs, meadows, and grasslands, which may benefit some faunal communities, but not others. We describe factors that limit and promote faunal resilience to shifting wildfire regimes for terrestrial and aquatic ecosystems. We highlight the potential value of interspersed nonforest patches to terrestrial wildlife. Similarly, we review watershed thresholds and factors that control the resilience of aquatic ecosystems to wildfire, mediated by thermal changes and chemical, debris, and sediment loadings. We present a 2-dimensional life history framework to describe temporal and spatial life history traits that species use to resist wildfire effects or to recover after wildfire disturbance at a metapopulation scale. The role of fire refuge is explored for metapopulations of species. In aquatic systems, recovery of assemblages postfire may be faster for smaller fires where unburned tributary basins or instream structures provide refuge from debris and sediment flows. We envision that more-frequent, lower-severity fires will favor opportunistic species and that less-frequent high-severity fires will favor better competitors. Along the spatial dimension, we hypothesize that fire regimes that are predictable and generate burned patches in close proximity to refuge will favor species that move to refuges and later recolonize, whereas fire regimes that tend to generate less-severely burned patches may favor species that shelter in place. Looking beyond the trees to forest fauna, we consider mitigation options to enhance resilience and buy time for species facing a no-analog future.

Ecology and Evolution↗
USGS2021

Space-for-time is not necessarily a substitution when monitoring the distribution of pelagic fishes in the San Francisco Bay-Delta

Occupancy models are often used to analyze long-term monitoring data to better understand how and why species redistribute across dynamic landscapes while accounting for incomplete capture. However, this approach requires replicate detection/non-detection data at a sample unit and many long-term monitoring programs lack temporal replicate surveys. In such cases, it has been suggested that surveying subunits within a larger sample unit may be an efficient substitution (i.e., space-for-time substitution). Still, the efficacy of fitting occupancy models using a space-for-time substitution has not been fully explored and is likely context dependent. Herein, we fit occupancy models to Delta Smelt ( Hypomesus transpacificus ) and Longfin Smelt ( Spirinchus thaleichthys ) catch data collected by two different monitoring programs that use the same sampling gear in the San Francisco Bay-Delta, USA. We demonstrate how our inferences concerning the distribution of these species changes when using a space-for-time substitution. Specifically, we found the probability that a sample unit was occupied was much greater when using a space-for-time substitution, presumably due to the change in the spatial scale of our inferences. Furthermore, we observed that as the spatial scale of our inferences increased, our ability to detect environmental effects on system dynamics was obscured, which we suspect is related to the tradeoffs associated with spatial grain and extent. Overall, our findings highlight the importance of considering how the unique characteristics of monitoring programs influences inferences, which has broad implications for how to appropriately leverage existing long-term monitoring data to understand the distribution of species.

Calfornia↗
USGS2022

Effects of weather variation on waterfowl migration: Lessons from a continental-scale generalizable avian movement and energetics model

We developed a continental energetics-based model of daily mallard ( Anas platyrhynchos ) movement during the non-breeding period (September to May) to predict year-specific migration and overwinter occurrence. The model approximates movements and stopovers as functions of metabolism and weather, in terms of temperature and frozen precipitation (i.e., snow). The model is a Markov process operating at the population level and is parameterized through a review of literature. We applied the model to 62 years of daily weather data for the non-breeding period. The average proportion of available habitat decreased as weather severity increased, with mortality decreasing as the proportion of available habitat increased. The most commonly used locations during the course of the non-breeding period were generally consistent across years, with the most inter-annual variation present in the overwintering area. Our model revealed that the distribution of mallards on the landscape changed more dramatically when the variation in daily available habitat was greater. The main routes for avian migration in North America were predicted by our simulations: the Atlantic, Mississippi, Central, and Pacific flyways. Our model predicted an average of 77.4% survivorship for the non-breeding period across all years (range = 76.4%–78.4%), with lowest survivorship during autumn (90.5 ± 1.4%), intermediate survivorship in winter (91.8 ± 0.7%), and greatest survivorship in spring (93.6 ± 1.1%). We provide the parameters necessary for exploration within and among other taxa to leverage the generalizability of this migration model to a broader expanse of bird species, and across a range of climate change and land use/land cover change scenarios.

Ecology and Evolution↗
USGS2022

Errors in aerial survey count data: Identifying pitfalls and solutions

Accurate estimates of animal abundance are essential for guiding effective management, and poor survey data can produce misleading inferences. Aerial surveys are an efficient survey platform, capable of collecting wildlife data across large spatial extents in short timeframes. However, these surveys can yield unreliable data if not carefully executed. Despite a long history of aerial survey use in ecological research, problems common to aerial surveys have not yet been adequately resolved. Through an extensive review of the aerial survey literature over the last 50 years, we evaluated how common problems encountered in the data (including nondetection, counting error, and species misidentification) can manifest, the potential difficulties conferred, and the history of how these challenges have been addressed. Additionally, we used a double-observer case study focused on waterbird data collected via aerial surveys and an online group (flock) counting quiz to explore the potential extent of each challenge and possible resolutions. We found that nearly three quarters of the aerial survey methodology literature focused on accounting for nondetection errors, while issues of counting error and misidentification were less commonly addressed. Through our case study, we demonstrated how these challenges can prove problematic by detailing the extent and magnitude of potential errors. Using our online quiz, we showed that aerial observers typically undercount group size and that the magnitude of counting errors increases with group size. Our results illustrate how each issue can act to bias inferences, highlighting the importance of considering individual methods for mitigating potential problems separately during survey design and analysis. We synthesized the information gained from our analyses to evaluate strategies for overcoming the challenges of using aerial survey data to estimate wildlife abundance, such as digital data collection methods, pooling species records by family, and ordinal modeling using binned data. Recognizing conditions that can lead to data collection errors and having reasonable solutions for addressing errors can allow researchers to allocate resources effectively to mitigate the most significant challenges for obtaining reliable aerial survey data.

Alabama, Florida, Louisiana, Mississippi, Texas↗
USGS2014

Guidelines for a priori grouping of species in hierarchical community models

Recent methodological advances permit the estimation of species richness and occurrences for rare species by linking species-level occurrence models at the community level. The value of such methods is underscored by the ability to examine the influence of landscape heterogeneity on species assemblages at large spatial scales. A salient advantage of community-level approaches is that parameter estimates for data-poor species are more precise as the estimation process borrows from data-rich species. However, this analytical benefit raises a question about the degree to which inferences are dependent on the implicit assumption of relatedness among species. Here, we assess the sensitivity of community/group-level metrics, and individual-level species inferences given various classification schemes for grouping species assemblages using multispecies occurrence models. We explore the implications of these groupings on parameter estimates for avian communities in two ecosystems: tropical forests in Puerto Rico and temperate forests in northeastern United States. We report on the classification performance and extent of variability in occurrence probabilities and species richness estimates that can be observed depending on the classification scheme used. We found estimates of species richness to be most precise and to have the best predictive performance when all of the data were grouped at a single community level. Community/group-level parameters appear to be heavily influenced by the grouping criteria, but were not driven strictly by total number of detections for species. We found different grouping schemes can provide an opportunity to identify unique assemblage responses that would not have been found if all of the species were analyzed together. We suggest three guidelines: (1) classification schemes should be determined based on study objectives; (2) model selection should be used to quantitatively compare different classification approaches; and (3) sensitivity of results to different classification approaches should be assessed. These guidelines should help researchers apply hierarchical community models in the most effective manner.

Ecology and Evolution↗
USGS2022

Parasites in kelp-forest food webs increase food-chain length, complexity, and specialization, but reduce connectance

We explored whether parasites are important in kelp forests by examining their effects on a high-quality, high-resolution kelp-forest food web. After controlling for generic effects of network size, parasites affected kelp-forest food web structure in some ways consistent with other systems. Parasites increased the trophic span of the web, increasing top predator vulnerability and the longest chain length. Unique links associated with parasites, such as concomitant predation (consumption of parasites along with their hosts by predators) increased the frequency of network motifs involving mutual consumption and decreased niche contiguity of free-living species. However, parasites also affected kelp-forest food web structure in ways not seen in other systems. Kelp-forest parasites are richer and more specialized than other systems. As a result, parasites reduced diet generality and decreased connectance in the kelp forest. Although mutual consumption motifs increased in frequency, this motif type was still a small fraction of all possible motifs, so their increase in frequency was not enough to compensate for the decrease in connectance caused by adding many specialist parasite species.

California↗
USGS2011

Modelling ecological flow regime: an example from the Tennessee and Cumberland River basins

Predictive equations were developed for 19 ecologically relevant streamflow characteristics within five major groups of flow variables (magnitude, ratio, frequency, variability, and date) for use in the Tennessee and Cumberland River basins using stepbackward regression. Basin characteristics explain 50% or more of the variation for 12 of the 19 equations. Independent variables identified through stepbackward regression were statistically significant in 78 of 304 cases (α > 0.0001) and represent four major groups: climate, physical landscape features, regional indicators, and land use. Of these groups, the regional and climate variables were the most influential for determining hydrologic response. Daily temperature range, geologic factor, and rock depth were major factors explaining the variability in 17, 15, and 13 equations, respectively. The equations and independent datasets were used to explore the broad relation between basin properties and streamflow and the implication of streamflow to the study of ecological flow requirements. Key results include a high degree of hydrologic variability among least disturbed Blue Ridge streams, similar hydrologic behaviour for watersheds with widely varying degrees of forest cover, and distinct hydrologic profiles for streams in different geographic regions. Published in 2011. This article is a US Government work and is in the public domain in the USA.

Alabama;Georgia;Kentucky;Mississippi;North Carolin↗
USGS2023

Evaluating the spatial and temporal variability of groundwater uptake by riparian vegetation in a humid southeastern US catchment

In environments with shallow water tables, vegetation may use groundwater to support transpiration (T G ). This process has been carefully studied in some arid climates but rarely in humid climates—even those with severe droughts and seasonal water deficits. As such, the role of T G in humid-catchment hydrology is poorly constrained. We analysed water table fluctuations from nine monitoring wells along three transects in a second-order forested catchment to estimate T G at plot and whole-riparian zone scales. Average T G estimated around all well locations ranged from 1.06 to 4.95 mm d −1 and did not change systematically as a function of distance from stream channel or with plot-scale tree basal area. Counter to some previous studies, we found that T G was greater when the water table depth was deeper. Furthermore, the pattern of T G with water table depth was not monotonic at all locations. The ratio of T G to potential evapotranspiration tended to increase over the growing season, reflecting the progressive decrease in soil moisture storage and a greater reliance by vegetation on groundwater. Due to the lack of consistent spatial patterns in T G , we explored the number of monitoring wells needed to consistently estimate average T G within the 95% confidence bounds of the true mean. Based on this analysis, six or more wells were needed to consistently fall within the 95% confidence interval of the true mean. While this is based on the observed variability at a single site, it provides information for others considering this approach in similar upland forested catchments in humid regions.

Ecohydrology↗
USGS2011

Understanding the role of ecohydrological feedbacks in ecosystem state change in drylands

Ecohydrological feedbacks are likely to be critical for understanding the mechanisms by which changes in exogenous forces result in ecosystem state change. We propose that in drylands, the dynamics of ecosystem state change are determined by changes in the type (stabilizing vs amplifying) and strength of ecohydrological feedbacks following a change in exogenous forces. Using a selection of five case studies from drylands, we explore the characteristics of ecohydrological feedbacks and resulting dynamics of ecosystem state change. We surmise that stabilizing feedbacks are critical for the provision of plant-essential resources in drylands. Exogenous forces that break these stabilizing feedbacks can alter the state of the system, although such changes are potentially reversible if strong amplifying ecohydrological feedbacks do not develop. The case studies indicate that if amplifying ecohydrological feedbacks do develop, they are typically associated with abiotic processes such as runoff, erosion (by wind and water), and fire. These amplifying ecohydrological feedbacks progressively modify the system in ways that are long-lasting and possibly irreversible on human timescales.

Ecohydrology↗
USGS2025

Filling the gaps: A Bayesian mixture model for imputing missing soil water content data

Soil water content (SWC) data are central to evaluating how soil moisture varies over time and space and influences critical plant and ecosystem functions, especially in water-limited drylands. However, sensors that record SWC at high frequencies often malfunction, leading to incomplete timeseries and limiting our understanding of dryland ecosystem dynamics. We developed an analytical approach to impute missing SWC data, which we tested at six eddy flux tower sites along an elevation gradient in the southwestern United States. We impute missing data as a mixture of linearly interpolated SWC between the observed endpoints of a missing data gap and SWC simulated by an ecosystem water balance model (SOILWAT2). Within a Bayesian framework, we allowed the relative utility (mixture weight) of each component (linearly interpolated vs. SOILWAT2) to vary by depth, site and gap characteristics. We explored “fixed” weights versus “dynamic” weights that vary as a function of cumulative precipitation, average temperature, and time since the start of the gap. Both models estimated missing SWC data well (R2 = 0.70–0.88 vs. 0.75–0.91 for fixed vs. dynamic weights, respectively), but the utility of linearly interpolated versus SOILWAT2 values depended on site and depth. SOILWAT2 was more useful for more arid sites, shallower depths, longer and warmer gaps and gaps that received greater precipitation. Overall, the mixture model reliably gap-fills SWC, while lending insight into processes governing SWC dynamics. This approach to impute missing data could be adapted to accommodate more than two mixture components and other types of environmental timeseries.

New Mexico↗
USGS2026

Stream temperature variability in headwater beaver dam complexes in relation to hydrologic and environmental factors

Beaver modify hydrological regimes and have the ability to both increase water storage and alter stream temperatures. For these reasons, beaver translocation and the construction of human engineered beaver-dam analogs (BDAs) have become popular tools for climate-change adaptation. However, there is a lack of understanding about how beaver engineering affects stream temperature. The results from previous studies vary considerably and the drivers of the discrepancies remain unclear. We investigated the longitudinal and vertical variation of stream temperature in and around 24 sites consisting of one or more beaver ponds across 17 headwater streams around the Methow and Okanogan river valleys of Washington State (USA). We then explored possible hydrologic and environmental drivers of observed thermal patterns. Despite considerable variation, we found that beaver ponds were often associated with an increase in downstream temperatures. The magnitude of this effect increased with total pond hydraulic height, which was directly related to the number and size of ponds per site. We also found that pond bottoms were cooler than upstream inflow sites for a period of time in the afternoon. Thus, although beaver dam complexes in the Methow River watershed do not consistently cool streams—and in fact often increase downstream temperatures—the bottoms of beaver ponds can create relatively cool water areas during the hottest part of the day. Furthermore, if managers choose to use beaver translocation or BDAs, locations with topography that would result in deeper ponds with more canopy cover may limit negative temperature effects on coldwater aquatic biota.

Washington↗
USGS2016

Somatic growth dynamics of West Atlantic hawksbill sea turtles: a spatio-temporal perspective

Somatic growth dynamics are an integrated response to environmental conditions. Hawksbill sea turtles (Eretmochelys imbricata) are long-lived, major consumers in coral reef habitats that move over broad geographic areas (hundreds to thousands of kilometers). We evaluated spatio-temporal effects on hawksbill growth dynamics over a 33-yr period and 24 study sites throughout the West Atlantic and explored relationships between growth dynamics and climate indices. We compiled the largest ever data set on somatic growth rates for hawksbills &ndash; 3541 growth increments from 1980 to 2013. Using generalized additive mixed model analyses, we evaluated 10 covariates, including spatial and temporal variation, that could affect growth rates. Growth rates throughout the region responded similarly over space and time. The lack of a spatial effect or spatio-temporal interaction and the very strong temporal effect reveal that growth rates in West Atlantic hawksbills are likely driven by region-wide forces. Between 1997 and 2013, mean growth rates declined significantly and steadily by 18%. Regional climate indices have significant relationships with annual growth rates with 0- or 1-yr lags: positive with the Multivariate El Ni&ntilde;o Southern Oscillation Index (correlation = 0.99) and negative with Caribbean sea surface temperature (correlation = &minus;0.85). Declines in growth rates between 1997 and 2013 throughout the West Atlantic most likely resulted from warming waters through indirect negative effects on foraging resources of hawksbills. These climatic influences are complex. With increasing temperatures, trajectories of decline of coral cover and availability in reef habitats of major prey species of hawksbills are not parallel. Knowledge of how choice of foraging habitats, prey selection, and prey abundance are affected by warming water temperatures is needed to understand how climate change will affect productivity of consumers that live in association with coral reefs. Main conclusions The decadal declines in growth rates between 1997 and 2013 throughout the West Atlantic most likely resulted from warming waters through indirect negative effects on the foraging resources of hawksbills. These climatic influences are complex. With increasing temperatures, the trajectories of decline of coral cover and availability in reef habitats of major prey species of hawksbills are not parallel. Knowledge of how choice of foraging habitats, prey selection, and prey abundance are affected by warming water temperatures is needed to understand how climate change will affect productivity of consumers that live in association with coral reefs.

Ecosphere↗
USGS2016

Forecasting the relative influence of environmental and anthropogenic stressors on polar bears

Effective conservation planning requires understanding and ranking threats to wildlife populations. We developed a Bayesian network model to evaluate the relative influence of environmental and anthropogenic stressors, and their mitigation, on the persistence of polar bears ( Ursus maritimus ). Overall sea ice conditions, affected by rising global temperatures, were the most influential determinant of population outcomes. Accordingly, unabated rise in atmospheric greenhouse gas (GHG) concentrations was the dominant influence leading to worsened population outcomes, with polar bears in three of four ecoregions reaching a dominant probability of decreased or greatly decreased by the latter part of this century. Stabilization of atmospheric GHG concentrations by mid-century delayed the greatly reduced state by &asymp;25 yr in two ecoregions. Prompt and aggressive mitigation of emissions reduced the probability of any regional population becoming greatly reduced by up to 25%. Marine prey availability, linked closely to sea ice trend, had slightly less influence on outcome state than sea ice availability itself. Reduced mortality from hunting and defense of life and property interactions resulted in modest declines in the probability of a decreased or greatly decreased population outcome. Minimizing other stressors such as trans-Arctic shipping, oil and gas exploration, and contaminants had a negligible effect on polar bear outcomes, although the model was not well-informed with respect to the potential influence of these stressors. Adverse consequences of loss of sea ice habitat became more pronounced as the summer ice-free period lengthened beyond four months, which could occur in most of the Arctic basin after mid-century if GHG emissions are not promptly reduced. Long-term conservation of polar bears would be best supported by holding global mean temperature to &le; 2&deg;C above preindustrial levels. Until further sea ice loss is stopped, management of other stressors may serve to slow the transition of populations to progressively worsened outcomes, and improve the prospects for their long-term persistence.

Ecosphere↗
USGS2016

Climate change is advancing spring onset across the U.S. national park system

Many U.S. national parks are already at the extreme warm end of their historical temperature distributions. With rapidly warming conditions, park resource management will be enhanced by information on seasonality of climate that supports adjustments in the timing of activities such as treating invasive species, operating visitor facilities, and scheduling climate-related events (e.g., flower festivals and fall leaf-viewing). Seasonal changes in vegetation, such as pollen, seed, and fruit production, are important drivers of ecological processes in parks, and phenology has thus been identified as a key indicator for park monitoring. Phenology is also one of the most proximate biological responses to climate change. Here, we use estimates of start of spring based on climatically modeled dates of first leaf and first bloom derived from indicator plant species to evaluate the recent timing of spring onset (past 10–30 yr) in each U.S. natural resource park relative to its historical range of variability across the past 112 yr (1901–2012). Of the 276 high latitude to subtropical parks examined, spring is advancing in approximately three-quarters of parks (76%), and 53% of parks are experiencing “extreme” early springs that exceed 95% of historical conditions. Our results demonstrate how changes in climate seasonality are important for understanding ecological responses to climate change, and further how spatial variability in effects of climate change necessitates different approaches to management. We discuss how our results inform climate change adaptation challenges and opportunities facing parks, with implications for other protected areas, by exploring consequences for resource management and planning.

Ecosphere↗