Geology topics

Research about North America

Source-linked reports with geographic coverage including North America.

At least 37 records · Page 2Linked to original sources

USGS2022

By land, air, and water — U.S. Geological Survey science supporting fish and wildlife migrations throughout North America

Countless species of animals—big game, birds, bats, insects, amphibians, reptiles, and fish—migrate to reach suitable habitats to feed, reproduce, and raise their young. Animal migrations developed over millennia commonly follow migration corridors—unique routes for each species—to move among seasonal habitats. Changes along those corridors, whether from human development (buildings, roads, dams) or from natural disturbances (for example, climate change, drought, fire, flooding, or invasive species), can make them harder to navigate. The U.S. Geological Survey’s Ecosystems Mission Area provides science that assists land managers in mapping, enhancing, protecting, and reconnecting migration corridors critical for diverse fish and wildlife populations that migrate, such as Odocoileus hemionus (mule deer) and Antilocapra americana (pronghorn), trout and salmon, salamanders, tortoises, bats, and Danaus plexippus (monarch butterflies).

North America↗

USGS2022

Machine learned daily life history classification using low frequency tracking data and automated modelling pipelines: Application to North American waterfowl

Background Identifying animal behaviors, life history states, and movement patterns is a prerequisite for many animal behavior analyses and effective management of wildlife and habitats. Most approaches classify short-term movement patterns with high frequency location or accelerometry data. However, patterns reflecting life history across longer time scales can have greater relevance to species biology or management needs, especially when available in near real-time. Given limitations in collecting and using such data to accurately classify complex behaviors in the long-term, we used hourly GPS data from 5 waterfowl species to produce daily activity classifications with machine-learned models using “automated modelling pipelines”. Methods Automated pipelines are computer-generated code that complete many tasks including feature engineering, multi-framework model development, training, validation, and hyperparameter tuning to produce daily classifications from eight activity patterns reflecting waterfowl life history or movement states. We developed several input features for modeling grouped into three broad categories, hereafter “feature sets”: GPS locations, habitat information, and movement history. Each feature set used different data sources or data collected across different time intervals to develop the “features” (independent variables) used in models. Results Automated modelling pipelines rapidly developed easily reproducible data preprocessing and analysis steps, identification and optimization of the best performing model and provided outputs for interpreting feature importance. Unequal expression of life history states caused unbalanced classes, so we evaluated feature set importance using a weighted F1-score to balance model recall and precision among individual classes. Although the best model using the least restrictive feature set (only 24 hourly relocations in a day) produced effective classifications (weighted F1 = 0.887), models using all feature sets performed substantially better (weighted F1 = 0.95), particularly for rarer but demographically more impactful life history states (i.e., nesting). Conclusions Automated pipelines generated models producing highly accurate classifications of complex daily activity patterns using relatively low frequency GPS and incorporating more classes than previous GPS studies. Near real-time classification is possible which is ideal for time-sensitive needs such as identifying reproduction. Including habitat and longer sequences of spatial information produced more accurate classifications but incurred slight delays in processing.

Movement Ecology↗

USGS2021

Galliform exclusion from the Migratory Bird Treaty Act has produced an alternate conservation path, but no evidence for differences in population status

The Migratory Bird Treaty Act (MBTA) is critical to avian conservation in the United States, both through its protection of migratory birds and as a catalyst for a century of coordinated avian conservation. While more than 1,000 species are protected by MBTA, of extant bird species native to the continental U.S., only 20 species belonging to the order Galliformes are explicitly excluded. Management of galliforms has occurred largely without direct federal oversight, placing this group on a fundamentally different conservation path during the century following MBTA passage. In this paper, we review the historical context and biological justification for exclusion of galliforms from MBTA and synthesize how their present-day conservation differs from that of migratory birds. We find the most prominent difference between the two groups involves the scope of coordination among stakeholders. The U.S. government, primarily via the Department of Interior, acts as de facto coordinating body for migratory bird conservation and plays the central role in oversight, funding, and administration of management in the United States. In contrast, galliform management falls primarily to individual state wildlife agencies, and coordinated conservation efforts have been more ad hoc and unevenly spread across species. Migratory birds benefit from an almost universally greater scope of research and monitoring, scale of habitat conservation, and sophistication of harvest management compared with galliforms. Galliform harvest management plans, in particular, are less likely to use measurable objectives, reporting of uncertainty in population parameters, and explanation of harvest management techniques. Based on a review of species status lists (e.g., the U.S. Endangered Species Act), we found no evidence that galliforms were more frequently listed than migratory species. Regional trend estimates from the North American Breeding Bird Survey (BBS) were more likely to be negative for galliforms over the period 1966–2015, but this was primarily driven by Northern Bobwhite ( Colinus virginianus ). Data to assess galliform population status are generally poor, which complicates assessment for roughly half of galliform species. Increased support for coordination among state agencies and other stakeholders, similar to that applied to migratory birds, could help to ensure that galliform conservation is poised to tackle forthcoming challenges associated with global change.

North America↗

USGS2021

The importance of wetland carbon dynamics to society: Insight from the Second State of the Carbon Cycle Science Report

The Second State of the Carbon Cycle Report (SOCCR2) culminated in 19 chapters that spanned all North American sectors – from Energy Systems to Agriculture and Land Use – known to be important for understanding carbon (C) cycling and accounting. Wetlands, both inland and coastal, were found to be significant components of C fluxes along the terrestrial to aquatic hydrologic continuum. In this chapter, we synthesize the role of wetlands in the overall C footprint of North America (from Canada to Mexico) as one metric of the societal values placed on these terrestrial-aquatic interfaces. We also summarize the effects of management activities and climate change on the wetland C cycle and give some perspectives on the current and future importance of wetlands to society.

Geophysical Monograph Series↗

USGS2021

The scope and severity of white-nose syndrome on hibernating bats in North America

Assessing the scope and severity of threats is necessary for evaluating impacts on populations to inform conservation planning. Quantitative threat assessment often requires monitoring programs that provide reliable data over relevant spatial and temporal scales, yet such programs can be difficult to justify until there is an apparent stressor. Leveraging efforts of wildlife management agencies to record winter counts of hibernating bats, we collated data for 5 species from over 200 sites across 27 U.S. states and 2 Canadian provinces from 1995 to 2018 to determine the impact of white-nose syndrome (WNS), a deadly disease of hibernating bats. We estimated declines of winter counts of bat colonies at sites where the invasive fungus that causes WNS ( Pseudogymnoascus destructans ) had been detected to assess the threat impact of WNS. Three species undergoing species status assessment by the U.S. Fish and Wildlife Service ( Myotis septentrionalis , Myotis lucifugus , and Perimyotis subflavus ) declined by more than 90%, which warrants classifying the severity of the WNS threat as extreme based on criteria used by NatureServe. The scope of the WNS threat as defined by NatureServe criteria was large (36% of Myotis lucifugus range) to pervasive (79% of Myotis septentrionalis range) for these species. Declines for 2 other species ( Myotis sodalis and Eptesicus fuscus ) were less severe but still qualified as moderate to serious based on NatureServe criteria. Data-sharing across jurisdictions provided a comprehensive evaluation of scope and severity of the threat of WNS and indicated regional differences that can inform response efforts at international, national, and state or provincial jurisdictions. We assessed the threat impact of an emerging infectious disease by uniting monitoring efforts across jurisdictional boundaries and demonstrated the importance of coordinated monitoring programs, such as the North American Bat Monitoring Program (NABat), for data-driven conservation assessments and planning.

Conservation Biology↗

USGS2021

First record of Najas marina (Hydrocharitaceae) for Montana and an update on the North American distribution

Three recent collections of Najas marina (spiny water-nymph) from Missoula County, Montana are documented and illustrated. These collections are the first records for Montana and for the Pacific Northwest region. The occurrence of N. marina in Montana reflects a significant northward expansion of this species in the Mountain West. The North American distribution of this species is also updated.

Phytoneuron↗

USGS2020

Model selection for the North American Breeding Bird Survey

The North American Breeding Bird Survey (BBS) provides data that can be used in complex, multiscale analyses of population change, while controlling for scale‐specific nuisance factors. Many alternative models can be fit to the data, but most model selection procedures are not appropriate for hierarchical models. Leave‐one‐out cross‐validation (LOOCV), in which relative model fit is assessed by omitting an observation and assessing the prediction of a model fit using the remainder of the data, provides a reasonable approach for assessing models, but is time consuming and not feasible to apply for all observations in large data sets. We report the first large‐scale formal model selection for BBS data, applying LOOCV to stratified random samples of observations from BBS data. Our results are for 548 species of North American birds, comparing the fit of four alternative models that differ in year effect structures and in descriptions of extra‐Poisson overdispersion. We use a hierarchical model among species to evaluate posterior probabilities that models are best for individual species. Models in which differences in year effects are conditionally independent (D models) were generally favored over models in which year effects are modeled by a slope parameter and a random year effect (S models), and models in which extra‐Poisson overdispersion effects are independent and t ‐distributed (H models) tended to be favored over models where overdispersion was independent and normally distributed. Our conclusions lead us to recommend a change from the conventional S model to D and H models for the vast majority of species (544/548). Comparison of estimated population trends based on the favored model relative to the S model currently used for BBS summaries indicates no consistent differences in estimated trends. Of the 18 species that showed large differences in estimated trends between models, estimated trends from the default S model were more extreme, reflecting the influence of the slope parameter in that model for species that are undergoing large population changes. WAIC, a computationally simpler alternative to LOOCV, does not appear to be a reliable alternative to LOOCV.

Ecological Applications↗

USGS2020

Assessing the risks posed by SARS-CoV-2 in and via North American bats — Decision framing and rapid risk assessment

The novel β-coronavirus, SARS-CoV-2, may pose a threat to North American bat populations if bats are exposed to the virus through interaction with humans, if the virus can subsequently infect bats and be transmitted among them, and if the virus causes morbidity or mortality in bats. Further, if SARS-CoV-2 became established in bat populations, it could possibly serve as a source for new infection in humans, domesticated animals, or other wild animals. Wildlife management agencies in the United States are concerned about these potential risks and have begun to issue guidance regarding work that brings humans into contact with bats, but decision making is difficult because of the high degree of uncertainty about many of the relevant processes that could lead to virus transmission and establishment. The risk assessment described in this report was undertaken to provide management agencies with an understanding of the likelihood that the various steps in the causal pathways would lead to SARS-CoV-2 infection of North American bats from people. This assessment focused on the active season for bats in the temperate zone of North America (April 15 through November 15), and used Myotis lucifugus (little brown bats) as a surrogate species. At the time of this work (April 2020), no empirical data about the effects of SARS-CoV-2 on North American bats were available, so a formal process of expert judgment was used to elicit estimates of the underlying parameters. Twelve experts in bat ecology, epidemiology, virology, and wildlife disease from the United States, United Kingdom, and Australia participated in the elicitation. A Monte Carlo simulation model was used to integrate the parameter estimates elicited from the experts and to predict the likelihood of exposure and infection in bats through a series of transmission pathways, with particular attention to capturing uncertainty in the predictions. Given the current state of knowledge as expressed by the expert panel, the results of this assessment indicate that there is a non-negligible risk of transmission of SARS-CoV-2 from humans to bats. For example, if a research scientist were shedding SARS-CoV-2 virus while handling bats under the field protocols used in North America prior to the COVID-19 pandemic, the risk model indicates that 50 percent (uncertainty, 15–84 percent) of those bats could be exposed to virus, and 17 percent (uncertainty, 3–51 percent) could become infected. Use of personal protective equipment, especially a respirator, is expected to reduce the exposure risk. The expert panel estimated that exposure risk from research scientists could be reduced 94–96 percent (uncertainty, 86–99 percent) through proper use of appropriate N95 respirators (a type of mechanical filter worn over the nose and mouth), dedicated clothing (such as Tyvek coveralls), and gloves. Should any North American bats become infected with SARS-CoV-2, the expert panel estimated that there is an approximately 33-percent chance the virus could spread within a bat population. This study, conducted by the U.S. Geological Survey in cooperation with the U.S. Fish and Wildlife Service, identified several critical uncertainties that could affect the estimate of risks associated with SARS-CoV-2 entering bat populations—notably, the underlying probability that a human would be shedding virus while working with bats, the likelihood of the virus replicating in bat tissue, and the likelihood of transmission of the virus within bat populations. Ongoing empirical work during May–October 2020 may shed light on these issues. Follow-up work is needed to better understand the probability of transmission of SARS-CoV-2 to bats from the general public; the manner in which the probabilities of exposure, infection, and transmission would differ during hibernation compared to the breeding season; and the likelihood of important effects, like morbidity and mortality in bats, the possibility of zoonosis from a North American bat reservoir, and effects of and on other wildlife.

North America↗

USGS2020

The effects of management practices on grassland birds—Merlin ( Falco columbarius )

The key to Merlin ( Falco columbarius ) management is maintaining an interspersion of groves of deciduous or coniferous trees for nesting and open grasslands for hunting. Merlins do not build their own nests but rather use former nests of other bird species, including those of corvids (crows, ravens, and magpies) and accipitrids (hawks). In recent decades, Merlins have established breeding populations in urban and residential areas in the northern Great Plains.

Professional Paper↗

USGS2020

Waterfowl occurrence and residence time as indicators of H5 and H7 avian influenza in North American Poultry

Avian inﬂuenza (AI) affects wild aquatic birds and poses hazards to human health, food security, and wildlife conservation globally. Accordingly, there is a recognized need for new methods and tools to help quantify the dynamic interaction between wild bird hosts and commercial poultry. Using satellite-marked waterfowl, we applied Bayesian joint hierarchical modeling to concurrently model species distributions, residency times, migration timing, and disease occurrence probability under an integrated animal movement and disease distribution modeling framework. Our results indicate that migratory waterfowl are positively related to AI occurrence over North America such that as waterfowl occurrence probability or residence time increase at a given location, so too does the chance of a commercial poultry AI outbreak. Analyses also suggest that AI occurrence probability is greatest during our observed waterfowl northward migration, and less during the southward migration. Methodologically, we found that when modeling disparate facets of disease systems at the wildlife-agriculture interface, it is essential that multiscale spatial patterns be addressed to avoid mistakenly inferring a disease process or disease-environment relationship from a pattern evaluated at the improper spatial scale. The study offers important insights into migratory waterfowl ecology and AI disease dynamics that aid in better preparing for future outbreaks.

Scientific Reports↗

USGS2020

Climate-change refugia in boreal North America: What, where, and for how long?

T The vast boreal biome plays an important role in the global carbon cycle but is experiencing particularly rapid climate warming, threatening the integrity of valued ecosystems and their component species. We developed a framework and taxonomy to identify climate‐change refugia potential in the North American boreal region, summarizing current knowledge regarding mechanisms, geographic distribution, and landscape indicators. While “terrain‐mediated” refugia will mostly be limited to coastal and mountain regions, the ecological inertia (resistance to external fluctuations) contained in some boreal ecosystems may provide more extensive buffering against climate change, resulting in “ecosystem‐protected” refugia. A notable example is boreal peatlands, which can retain high surface soil moisture and water tables even in the face of drought. Refugia from wildfire are also especially important in the boreal region, which is characterized by active disturbance regimes. Our framework will help identify areas of high refugia potential, and inform ecosystem management and conservation planning in light of climate change.

North America↗

USGS2020

Does signal-free detrending increase chronology coherence in large tree-ring networks?

Over the past decade, dendrochronologists have increasingly adopted the signal-free detrending (SFD) method to remove age-size trends in tree-ring measurement series, amplify the common stand-wide signal in composite chronologies, and recover medium- to low-frequency patterns that may be inadvertently removed by other detrending approaches. However, since its introduction in 2008, no systematic evaluation of the effects of SFD on tree-ring chronologies has been performed. Here we conduct the first review of SFD in dendrochronology and assess its effects when applied to large tree-ring networks. We analyzed the PAGES North America 2 K database of nearly 300 temperature-sensitive chronologies and the Missouri River database of over 350 chronologies curated for the purpose of reconstructing Missouri River streamflow. Both databases contain multiple versions of each chronology generated by different detrending methods, including those produced with (and without) the signal-free procedure applied. We evaluated (i) whether SFD increases chronology coherence at the site level by boosting the between-tree agreement, (ii) whether SFD increases coherence on a regional basis by making neighboring chronologies more similar to each other, and (iii) whether signal-free chronologies retained more medium- to low-frequency variability than their traditional counterparts. We find that, while SFD increased the strength of common signals in many instances, the effect was not universal and some sites even show a decrease in signal coherence. At regional scales, SFD increases chronology coherence in temperature-sensitive records but had no detectable effect on moisture-sensitive records. Our results demonstrate the importance of evaluating the effects of SFD prior to deploying this method for chronology development and paleoclimate reconstruction.

Dendrochronologia↗

USGS2020

Characterizing spatiotemporal patterns of crop phenology across North America during 2000–2016 using satellite imagery and agricultural survey data

Crop phenology represents an integrative indicator of climate change and plays a vital role in terrestrial carbon dynamics and sustainable agricultural development. However, spatiotemporal variations of crop phenology remain unclear at large scales. This knowledge gap has hindered our ability to realistically quantify the biogeochemical dynamics in agroecosystems, predict future climate, and make informed decisions for climate change mitigation and adaptation. In this study, we improved an EVI-curve-based approach and used it to detect spatiotemporal patterns in cropping intensity and five major phenological stages over North America during 2000–2016 using vegetation index in combination with agricultural survey data and other ancillary maps. Our predicted crop phenological stages showed strong linear relationships with the survey-based datasets, with R 2 , RMSEs, and MAEs in the ranges of 0.35 –0.99, three to ten days, and two to eight days, respectively. During the study period, the planting dates were advanced by 0.60 days/year ( p < 0.01), and harvesting dates were delayed by 0.78 days/year ( p < 0.01) over North America. A minimum temperature increase by 1 °C caused a 4.26-day planting advance (r = −0.50, p < 0. 01) or a 0.66-day harvest delay (r = 0.10, p < 0.01). While, a higher maximum temperature resulted in a planting advance by 4.48 days/°C (r = −0.62, p < 0.01) or a harvest advance by 2.22 days/°C (r = −0.40, p < 0.01). Our analysis illustrated evident spatiotemporal variations in crop phenology in response to climate change and management practices. The derived crop phenological datasets and cropping intensity maps can be used in regional climate assessments and in developing adaptation strategies.

ISPRS Journal of Photogrammetry and Remote Sensing↗

USGS2020

Dynamics, variability, and change in seasonal precipitation reconstructions for North America

Cool and warm season precipitation totals have been reconstructed on a gridded basis for North America using 439 tree-ring chronologies correlated with December-April totals and 547 different chronologies correlated with May-July totals. These discrete seasonal predictor chronologies are not significantly correlated with the alternate season and the reconstructions calibrate at least 40% of the variance in both December-April and May-July precipitation totals over a large portion of North America for up to 2,000-years. Validation statistics computed on independent instrumental precipitation data from 1901-1927 indicate that the December-April reconstructions are reliable over most of the western and southern United States and northcentral Mexico, and the May-July estimates are valid over most of the United States, southwest Canada, and northeast Mexico. The strong continent wide El Niño/Southern Oscillation (ENSO) signal embedded in the cool season reconstructions, and the Arctic Oscillation signal registered by the warm season estimates, both faithfully reproduce the sign, intensity, and spatial patterns of these ocean-atmospheric influences on North American precipitation as recorded with instrumental data. The reconstructions are included in the North American Seasonal Precipitation Atlas (NASPA) and provide new insight into decadal droughts and pluvials. They indicate that the 16th century megadrought, the most severe and sustained North American drought of the past 500-years, was the combined result of three distinct seasonal droughts each bearing unique spatial patterns potentially associated with seasonal forcing from ENSO, the Arctic Oscillation, and the Atlantic Multidecadal Oscillation. Significant 200- to 500-year long trends toward increased precipitation have been detected in the cool and warm season reconstructions for eastern North America. These seasonal precipitation changes appear to be part of the positive moisture trend measured in other paleoclimate proxies for the East that began due to natural forcing before the industrial revolution and may have recently been enhanced by anthropogenic climate change.

Journal of Climate↗

USGS2019

Visualizing populations of North American sea ducks: Maps to guide research and management planning

North American sea ducks generally breed in mid- to northern-latitude regions and nearly all rely upon marine habitats for much of their annual cycle. Most sea duck species remained poorly studied until the 1990s when declines were noted in several species and populations. Subsequent research, much of which was funded by the Sea Duck Joint Venture, began in the late 1990s with an emphasis on defining use areas throughout the annual cycle, migration patterns, and determining if there were distinct populations, within species, across North America. These studies relied largely upon satellite telemetry information to identify winter, breeding, and molting areas of sea ducks. New information from band recovery and genetic markers was added, contributing to hypotheses and initial conclusions about population delineation. Information on population units across North America is critical for identifying appropriate scales for evaluating population status and trends through annual monitoring surveys, harvest assessments, habitat protection and measuring effectiveness of management applications. Previous descriptions of population segments were for single species or smaller groups of similar species. Here, we summarize current knowledge on the general distribution and population segments of 13 species of sea ducks in North America by comparing range maps to long-term band recovery, genetic, and satellite telemetry data to inform population delineation assessments and future research. These comparisons show a high degree of consistency in population patterns for most species across the independent data types. These maps provide a foundation for developing new hypothesis-driven research to address remaining knowledge gaps and questions about population differentiation, annual cycle distribution, habitat use, and harvest assessment.

North America↗

USGS2019

Coast to coast: High genomic connectivity in North American scoters

Dispersal shapes demographic processes and therefore is fundamental to understanding biological, ecological, and evolutionary processes acting within populations. However, assessing population connectivity in scoters ( Melanitta sp.) is challenging as these species have large spatial distributions that span remote landscapes, have varying nesting distributions (disjunct vs. continuous), exhibit unknown levels of dispersal, and vary in the timing of the formation of pair bonds (winter vs. fall/spring migration) that may influence the distribution of genetic diversity. Here, we used double‐digest restriction‐associated DNA sequence (ddRAD) and microsatellite genotype data to assess population structure within the three North American species of scoter (black scoter, M. americana ; white‐winged scoter, M. deglandi ; surf scoter, M. perspicillata ), and between their European congeners (common scoter, M. nigra ; velvet scoter, M. fusca ). We uncovered no or weak genomic structure (ddRAD Φ ST < 0.019; microsatellite F ST < 0.004) within North America but high levels of structure among European congeners (ddRAD Φ ST > 0.155, microsatellite F ST > 0.086). The pattern of limited genomic structure within North America is shared with other sea duck species and is often attributed to male‐biased dispersal. Further, migratory tendencies (east vs. west) of female surf and white‐winged scoters in central Canada are known to vary across years, providing additional opportunities for intracontinental dispersal and a mechanism for the maintenance of genomic connectivity across North America. In contrast, the black scoter had relatively elevated levels of divergence between Alaska and Atlantic sites and a second genetic cluster found in Alaska at ddRAD loci was concordant with its disjunct breeding distribution suggestive of a dispersal barrier (behavioral or physical). Although scoter populations appear to be connected through a dispersal network, a small percentage (<4%) of ddRAD loci had elevated divergence which may be useful in linking areas (nesting, molting, staging, and wintering) throughout the annual cycle.

North America↗

USGS2019

The integrated monarch monitoring program: From design to implementation

Steep declines in North American monarch butterfly ( Danaus plexippus ) populations have prompted continent-wide conservation efforts. While monarch monitoring efforts have existed for years, we lack a comprehensive approach to monitoring population vital rates integrated with habitat quality to inform adaptive management and effective conservation strategies. Building a geographically and ecologically representative dataset of monarchs and their habitat will improve these efforts. These data will help track long-term changes in the distribution and abundance of monarchs and their habitats, refine population and habitat models, and illuminate how conservation activities affect monarchs and their habitats. The Monarch Conservation Science Partnership developed the Integrated Monarch Monitoring Program (IMMP) to profile breeding habitats and their use by monarchs in North America. A spatially balanced random sampling framework guides site selection, while also allowing opportunistic inclusion of sites chosen by participants, such as conservation areas. The IMMP weaves new protocols together with those from existing monitoring programs to improve data compatibility for assessing milkweed (Asclepias spp.) density, nectar resources, monarch reproduction and survival, and adult monarch habitat use. Participants may select a protocol subset according to interests or local monitoring objectives, thereby maximizing contributions. Conservation partners, including public and private land managers, academic researchers, and citizen scientists contribute data to a national dataset available for analyses at multiple scales. We describe the program and its development, implementation elements that make the program robust and feasible, participation to date, and how IMMP data can advance research and conservation for monarchs, pollinators, and their habitats.

North America↗

USGS2019

Investigating (a)symmetry in a small mammal’s response to warmingand cooling events across western North America over the late Quaternary

Many mammalian populations conform spatially and temporally to Bergmann’s rule. This ecogeographic pattern is driven by selection for larger body masses by cooler temperatures and smaller ones by warming temperatures. However, it is unclear whether the response to warming or cooling temperatures is (a)symmetrical. Studies of the evolutionary record suggest that mammals evolve smaller body sizes more rapidly than larger ones, suggesting that it may be “easier” to adapt to warmingclimates than cooling ones. Here, we examine the potential asymmetrical response of mammals to past temperature fluctuations.We use the fossil midden record of the bushy-tailed woodrat, Neotoma cinerea, a well-studied animal that generally conforms to Bergmann’s rule, to test the ability of populations to respond to warming versus cooling climate throughout its modern range in western North America over the late Quaternary.We quantified the response to temperature change, as characterized by the Greenland Ice Sheet Project 2 temperature record, using N. cinerea presence/absence and “darwins.” Ourresults show that populations within the modern range of N. cinerea show little difference between warming and cooling events. However, northern, peripheral populations are absent during older, cooler periods, possibly due to climate or taphonomy. Our study suggests adaptation in situ may be an underestimated response to future climate change.

Quaternary Research↗