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At least 127 records · Page 7Linked to original sources
USGS2013

The Malthusian-Darwinian dynamic and the trajectory of civilization

Two interacting forces influence all populations: the Malthusian dynamic of exponential growth until resource limits are reached, and the Darwinian dynamic of innovation and adaptation to circumvent these limits through biological and/or cultural evolution. The specific manifestations of these forces in modern human society provide an important context for determining how humans can establish a sustainable relationship with the finite Earth.

Trends in Ecology and Evolution↗
USGS2023

Towards a better future for biodiversity and people: Modelling Nature Futures

The Nature Futures Framework (NFF) is a heuristic tool for co-creating positive futures for nature and people. It seeks to open up a diversity of futures through mainly three value perspectives on nature – Nature for Nature, Nature for Society, and Nature as Culture. This paper describes how the NFF can be applied in modelling to support decision-making. First, we describe key considerations for the NFF in developing qualitative and quantitative scenarios: i) multiple value perspectives on nature as a state space where pathways improving nature toward a frontier can be represented, ii) mutually reinforcing key feedbacks of social-ecological systems that are important for nature conservation and human wellbeing, iii) indicators of multiple knowledge systems describing the evolution of complex social-ecological dynamics. We then present three approaches to modelling Nature Futures scenarios in the review, screening, and design phases of policy processes. This paper seeks to facilitate the integration of relational values of nature in models and strengthen modelled linkages across biodiversity, nature’s contributions to people, and quality of life.

Global Environmental Change↗
USGS2017

The evolution of different maternal investment strategies in two closely related desert vertebrates

We compared egg size phenotypes and tested several predictions from the optimal egg size (OES) and bet-hedging theories in two North American desert-dwelling sister tortoise taxa, Gopherus agassizii and G. morafkai , that inhabit different climate spaces: relatively unpredictable and more predictable climate spaces, respectively. Observed patterns in both species differed from the predictions of OES in several ways. Mean egg size increased with maternal body size in both species. Mean egg size was inversely related to clutch order in G. agassizii , a strategy more consistent with the within-generation hypothesis arising out of bet-hedging theory or a constraint in egg investment due to resource availability, and contrary to theories of density dependence, which posit that increasing hatchling competition from later season clutches should drive selection for larger eggs. We provide empirical evidence that one species, G. agassizii , employs a bet-hedging strategy that is a combination of two different bet-hedging hypotheses. Additionally, we found some evidence for G. morafkai employing a conservative bet-hedging strategy. (e.g., lack of intra- and interclutch variation in egg size relative to body size). Our novel adaptive hypothesis suggests the possibility that natural selection favors smaller offspring in late-season clutches because they experience a more benign environment or less energetically challenging environmental conditions (i.e., winter) than early clutch progeny, that emerge under harsher and more energetically challenging environmental conditions (i.e., summer). We also discuss alternative hypotheses of sexually antagonistic selection, which arise from the trade-offs of son versus daughter production that might have different optima depending on clutch order and variation in temperature-dependent sex determination (TSD) among clutches. Resolution of these hypotheses will require long-term data on fitness of sons versus daughters as a function of incubation environment, data as yet unavailable for any species with TSD.

Arizona, California↗
USGS2020

The elephant in the lab (and field): Contamination in aquatic environmental DNA studies

The rapid evolution of environmental (e)DNA methods has resulted in knowledge gaps in smaller, yet critical details like proper use of negative controls to detect contamination. Detecting contamination is vital for confident use of eDNA results in decision-making. We conducted two literature reviews to summarize (a) the types of quality assurance measures taken to detect contamination of eDNA samples from aquatic environments, (b) the occurrence, frequency and attribution (i.e., putative sources) of unexpected amplification in these quality assurance samples, and (c) how results were interpreted when contamination occurred. In the first literature review, we reviewed 156 papers and found that 91% of targeted and 73% of metabarcoding eDNA studies reported inclusion of negative controls within their workflows. However, a large percentage of targeted (49%) and metabarcoding (80%) studies only reported negative controls for laboratory procedures, so results were potentially blind to field contamination. Many of the 156 studies did not provide critical methodological information and amplification results of negative controls. In our second literature review, we reviewed 695 papers and found that 30 targeted and 32 metabarcoding eDNA studies reported amplification of negative controls. This amplification occurred at similar proportions for field and lab workflow steps in targeted and metabarcoding studies. These studies most frequently used amplified negative controls to delimit a detection threshold above which is considered significant or provided rationale for why the unexpected amplifications did not affect results. In summary, we found that there has been minimal convergence over time on negative control implementation, methods, and interpretation, which suggests that increased rigor in these smaller, yet critical details remains an outstanding need. We conclude our review by highlighting several studies that have developed especially effective quality assurance, control and mitigation methods.

Frontiers in Ecology and Evolution↗
USGS2023

Host vs. pathogen evolutionary arms race: Effects of exposure history on individual response to a genetically diverse pathogen

Introduction: Throughout their range, bighorn sheep ( Ovis canadensis ) populations have seen significant disease-associated declines. Unfortunately, understanding of the underlying epidemiological processes driving the disease dynamics in this species has hindered conservation efforts aimed at improving the health and long-term viability of these populations. Individual response to pathogen exposure emerges from dynamic interactions between competing evolutionary processes within the host and pathogen. The host’s adaptive immune system recognizes pathogens and mounts a defensive response. Pathogens have evolved strategies to overcome adaptive immune defenses including maintaining high genetic diversity through rapid evolution. The outcomes of this evolutionary warfare determine the success of pathogen invasion of the host and ultimately the success of conservation efforts. Methods: During an epizootic dominated by a single strain, we explore these host-pathogen dynamics by examining the variation in effects of pathogen invasion on captive bighorn sheep with differing histories of exposure to genetically diverse strains of Mycoplasma ovipneumoniae (Movi). We monitored clinical signs of disease and sampled animals and their environment to detect spread of Movi among 37 bighorn sheep separated into nine pens based on known exposure Results: We documented Movi transmission within and across pens and we detected Movi DNA in air, water, and invertebrate samples. Higher levels of antibody to Movi prior to the epizootic were associated with a lower likelihood of presenting clinical signs of pneumonia. Nonetheless, higher antibody levels in symptomatic individuals were associated with more severe progressive disease, increased probability and speed of pneumonia-induced mortality, and reduced likelihood of returning to a healthy state. Bighorn sheep with previous exposure to a strain other than the predominant epizootic strain were more likely to recover. Discussion: Our results indicate that Movi-strain variability was sufficient to overwhelm the adaptive host immunological defenses. This outcome indicates, in free-ranging herds, past exposure is likely insufficient to protect bighorn sheep from infection by new Movi strains, although it influences the progression of disease and recovery within the herd. Therefore, given Movi-strain variability and the lack of immunological protection from past exposure, focusing management efforts on minimizing the introduction of Movi into bighorn herds, through separation of domestic and bighorn sheep and avoidance of management activities that create commingling of bighorn sheep carrying differing Movi strains, will likely be the most effective approach for reducing the effects of disease and achieving bighorn sheep conservation goals.

Idaho, Oregon, South Dakota, Washington↗
USGS2023

Supervised versus unsupervised approaches to classification of accelerometry data

Sophisticated animal-borne sensor systems are increasingly providing novel insight into how animals behave and move. Despite their widespread use in ecology, the diversity and expanding quality and quantity of data they produce have created a need for robust analytical methods for biological interpretation. Machine learning tools are often used to meet this need. However, their relative effectiveness is not well known and, in the case of unsupervised tools, given that they do not use validation data, their accuracy can be difficult to assess. We evaluated the effectiveness of supervised ( n = 6), semi-supervised ( n = 1), and unsupervised ( n = 2) approaches to analyzing accelerometry data collected from critically endangered California condors ( Gymnogyps californianus ). Unsupervised K-means and EM (expectation–maximization) clustering approaches performed poorly, with adequate classification accuracies of <0.8 but very low values for kappa statistics (range: −0.02 to 0.06). The semi-supervised nearest mean classifier was moderately effective at classification, with an overall classification accuracy of 0.61 but effective classification only of two of the four behavioral classes. Supervised random forest (RF) and k-nearest neighbor (kNN) machine learning models were most effective at classification across all behavior types, with overall accuracies >0.81. Kappa statistics were also highest for RF and kNN, in most cases substantially greater than for other modeling approaches. Unsupervised modeling, which is commonly used for the classification of a priori-defined behaviors in telemetry data, can provide useful information but likely is instead better suited to post hoc definition of generalized behavioral states. This work also shows the potential for substantial variation in classification accuracy among different machine learning approaches and among different metrics of accuracy. As such, when analyzing biotelemetry data, best practices appear to call for the evaluation of several machine learning techniques and several measures of accuracy for each dataset under consideration.

Ecology and Evolution↗
USGS2023

Four conservation challenges and a synthesis

Conservation and management of biological systems involves decision-making over time, with a generic goal of sustaining systems and their capacity to function in the future. We address four persistent and difficult conservation challenges: (1) prediction of future consequences of management, (2) uncertainty about the system's structure, (3) inability to observe ecological systems fully, and (4) nonstationary system dynamics. We describe these challenges in terms of dynamic systems subject to different sources of uncertainty, and we present a basic Markovian framework that can encompass approaches to all four challenges. Finding optimal conservation strategies for each challenge requires issue-specific structural features, including adaptations of state transition models, uncertainty metrics, valuation of accumulated returns, and solution methods. Strategy valuation exhibits not only some remarkable similarities among approaches but also some important operational differences. Technical linkages among the models highlight synergies in solution approaches, as well as possibilities for combining them in particular conservation problems. As methodology and computing software advance, such an integrated conservation framework offers the potential to improve conservation outcomes with strategies to allocate management resources efficiently and avoid negative consequences.

Ecology and Evolution↗
USGS2023

Growth, drought response, and climate-associated genomic structure in whitebark pine in the Sierra Nevada of California

Whitebark pine ( Pinus albicaulis Engelm.) has experienced rapid population declines and is listed as threatened under the Endangered Species Act in the United States. Whitebark pine in the Sierra Nevada of California represents the southernmost end of the species' distribution and, like other portions of its range, faces threats from an introduced pathogen, native bark beetles, and a rapidly warming climate. Beyond these chronic stressors, there is also concern about how this species will respond to acute stressors, such as drought. We present patterns of stem growth from 766 large (average diameter at breast height >25 cm), disease-free whitebark pine across the Sierra Nevada before and during a recent period of drought. We contextualize growth patterns using population genomic diversity and structure from a subset of 327 trees. Sampled whitebark pine generally had positive to neutral stem growth trends from 1970 to 2011, which was positively correlated with minimum temperature and precipitation. Indices of stem growth during drought years (2012 to 2015) relative to a predrought interval were mostly positive to neutral at our sampled sites. Individual tree growth response phenotypes appeared to be linked to genotypic variation in climate-associated loci, suggesting that some genotypes can take better advantage of local climatic conditions than others. We speculate that reduced snowpack during the 2012 to 2015 drought years may have lengthened the growing season while retaining sufficient moisture to maintain growth at most study sites. Growth responses may differ under future warming, however, particularly if drought severity increases and modifies interactions with pests and pathogens.

California, Nevada↗
USGS2023

Effects of population density and environmental conditions on life-history prevalence in a migratory fish

Individual variation in life-history traits can have important implications for the ability of populations to respond to environmental variability and change. In migratory animals, flexibility in the timing of life-history events, such as juvenile emigration from natal areas, can influence the effects of population density and environmental conditions on habitat use and population dynamics. We evaluated the functional relationships between population density and environmental covariates and the abundance of juveniles expressing different life-history pathways in a migratory fish, Chinook salmon ( Oncorhynchus tshawytscha ), in the Wenatchee River basin in Washington State, USA. We found that the abundance of younger emigrants from natal streams was best described by an accelerating or near-linear function of spawners, whereas the abundance of older emigrants was best described by a decelerating function of spawners. This supports the hypothesis that emigration timing varies in response to density in natal areas, with younger-emigrating life-history pathways comprising a larger proportion of emigrants when densities of conspecifics are high. We also observed positive relationships between winter stream discharge and abundance of younger emigrants, supporting the hypothesis that habitat conditions can also influence the prevalence of different life-history pathways. Our results suggest that early emigration, and a resultant increase in the use of downstream rearing habitats, may increase at higher population densities and with greater winter precipitation. Winter precipitation is projected to increase in this system due to climate warming. Characterizing relationships between life-history prevalence and environmental conditions may improve our understanding of species habitat requirements and is a first step in understanding the dynamics of species with diverse life-history strategies. As environmental conditions change—due to climate change, management, or other factors—resultant life-history changes are likely to have important demographic implications that will be challenging to predict when life-history diversity is not accounted for in population models.

Washington↗
USGS2023

Is now the time? Review of genetic rescue as a conservation tool for brook trout

Brook trout populations have been declining throughout their native range in the east coast of the United States. Many populations are now distributed in small, isolated habitat patches where low genetic diversity and high rates of inbreeding reduce contemporary viability and long-term adaptive potential. Although human-assisted gene flow could theoretically improve conservation outcomes through genetic rescue, there is widespread hesitancy to use this tool to support brook trout conservation. Here, we review the major uncertainties that have limited genetic rescue from being considered as a viable conservation tool for isolated brook trout populations and compare the risks of genetic rescue with other management alternatives. Drawing on theoretical and empirical studies, we discuss methods for implementing genetic rescue in brook trout that could yield long-term evolutionary benefits while avoiding negative fitness effects associated with outbreeding depression and the spread of maladapted alleles. We also highlight the potential for future collaborative efforts to accelerate our understanding of genetic rescue as a viable tool for conservation. Ultimately, while we acknowledge that genetic rescue is not without risk, we emphasize the merits that this tool offers for protecting and propagating adaptive potential and improving species' resilience to rapid environmental change.

Ecology and Evolution↗
USGS2023

Hidden Markov movement models reveal diverse seasonal movement patterns in two North American ungulates

Animal movement is the mechanism connecting landscapes to fitness, and understanding variation in seasonal animal movements has benefited from the analysis and categorization of animal displacement. However, seasonal movement patterns can defy classification when movements are highly variable. Hidden Markov movement models (HMMs) are a class of latent-state models well-suited to modeling movement data. Here, we used HMMs to assess seasonal patterns of variation in the movement of pronghorn ( Antilocapra americana ), a species known for variable seasonal movements that challenge analytical approaches, while using a population of mule deer ( Odocoileus hemionus ), for whom seasonal movements are well-documented, as a comparison. We used population-level HMMs in a Bayesian framework to estimate a seasonal trend in the daily probability of transitioning between a short-distance local movement state and a long-distance movement state. The estimated seasonal patterns of movements in mule deer closely aligned with prior work based on indices of animal displacement: a short period of long-distance movements in the fall season and again in the spring, consistent with migrations to and from seasonal ranges. We found seasonal movement patterns for pronghorn were more variable, as a period of long-distance movements in the fall was followed by a winter period in which pronghorn were much more likely to further initiate and remain in a long-distance movement pattern compared with the movement patterns of mule deer. Overall, pronghorn were simply more likely to be in a long-distance movement pattern throughout the year. Hidden Markov movement models provide inference on seasonal movements similar to other methods, while providing a robust framework to understand movement patterns on shorter timescales and for more challenging movement patterns. Hidden Markov movement models can allow a rigorous assessment of the drivers of changes in movement patterns such as extreme weather events and land development, important for management and conservation.

Wyoming↗
USGS2023

Confirmation of significant sea turtle nesting activity on a remote island chain in the Gulf of Mexico

Globally, six of the seven sea turtle species are threatened or endangered and as such, monitoring reproductive activity for these species is necessary for effective population recovery. Remote beaches provide a challenge to conducting these surveys, which often results in data gaps that can hamper management planning. Throughout the summer of 2022, aerial surveys were conducted over the Chandeleur Islands in the Gulf of Mexico. Turtle crawls were photographed for subsequent review by 10 expert observers. Whenever possible, ground surveys were conducted, and samples of unhatched eggs or dead hatchlings were collected. A summary of historic reports of sea turtle nesting activity at this site was also compiled. On 11 days between May 4, 2022, and July 30, 2022, photographs of 55 potential sea turtle crawls were taken. Observers identified 54 of those as being made by a sea turtle. There was high-to-moderate certainty that 16 of those crawls were nests, that 14 were made by loggerheads, and that two were made by Kemp's ridleys. Observers were least certain of species identification when surveys were conducted during rainy weather. Genetic analyses based on mitochondrial and nuclear DNA were conducted on samples from five nests and those analyses confirmed that three nests were laid by Kemp's ridleys and two were laid by loggerheads. Historic records from the Chandeleur Islands substantiate claims that the Chandeleurs have supported sea turtle nesting activity for decades; however, the consistency of this activity remains unknown. Our aerial surveys, particularly when coupled with imaging, were a useful tool for documenting nesting activity on these remote islands. Future monitoring programs at this site could benefit from a standardized aerial survey program with a seaplane so trends in nesting activity could be determined particularly as the beach undergoes restoration.

Louisiana↗
USGS2023

Fecal metabarcoding of the endangered Pacific pocket mouse (Perognathus longimembris pacificus) reveals a diverse and forb rich diet that reflects local habitat availability

Information on diet breadth and preference can assist in understanding links between food resources and population growth and inform habitat restoration for rare herbivores. We assessed the diet of the endangered Pacific pocket mouse using metabarcoding of fecal samples and compared it to plant community composition in long-term study plots in two populations on Marine Corps Base Camp Pendleton, San Diego County, CA. Fecal samples ( n = 221) were collected between spring 2016 and fall 2017 during monthly live-trap surveys. Concurrently, percent cover and plant phenology were measured in plots centered on trap locations. Fecal samples were sequenced with paired-end reads of the internal transcribed spacer 2 region of the nuclear ribosomal gene, and the resulting amplicons were matched to a regionally specific database. Seventy-three plant taxa were detected, which were mostly forbs and perennial herbs (70–90%). Diet composition differed between populations, years, seasons, and plots. Overall, diet and local habitat composition in plots were significantly correlated. However, we detected some differences in above-ground seed availability and proportion in fecal samples that indicate diet preferences for some forbs, perennial herbs, and native bunch grasses over perennial shrubs and non-native grasses. This is the first study of PPM to pair plant phenology surveys with diet metabarcoding to estimate resource selection, and results suggest that managing habitat for diverse native forb communities and reducing non-native grass cover may be beneficial for this critically endangered species.

California↗
USGS2023

Lesser Prairie-chicken incubation behavior and nest success most influenced by nest vegetation structure

Incubation breaks are necessary for any nesting bird but can increase the mortality risk of the nest or attending parent. How intrinsic and extrinsic variables affect nest attentiveness—the proportion of time a female is on nest during incubation— and subsequent survival of the nest remains unclear for uniparental species. We related female nest attentiveness to nest survival and tested the effects of intrinsic and extrinsic variables on nest attentiveness by female Lesser Prairie-chickens ( Tympanuchus pallidicinctus ) using GPS locations of 87 females at 109 nest sites in 3 study areas in Kansas during 2013–2015. Daily nest survival increased by 39% when nest attentiveness increased from 21% to 98%. Female Lesser Prairie-chickens were 18% less attentive as body mass increased from 600 to 920 g. Daily precipitation and temperature, controlled for days into the incubation period, had interactive effects on nest attentiveness with nest attentiveness lowest on cool, wet days and increasing as temperature increased, regardless of precipitation (41% attentiveness at 16°C and 79 mm of precipitation to 90% attentiveness at 37°C and 41 mm of precipitation). Nest attentiveness increased by 11% as the quantity of grass at the nest site increased from 5% to 78% when visual obstruction was at 1 and 2 decimeters (dm) and increased 9% as the quantity of grass at the nest site increased from 5% to 83% when visual obstruction was at its maximum (3 dm). Our findings reveal the critical importance of nest attentiveness and incubation behavior, not only in relation to demography, but within the context of changing environmental conditions. As warmer temperatures and extreme precipitation events become more common and change the growth rates of vegetation, species like the Lesser Prairie-chicken that are ground-nesting, rely on vegetation cover, and exhibit uniparental care could experience negative demographic consequences.

Kansas↗
USGS2023

Evaluating the utility of effective breeding size estimates for monitoring sea lamprey spawning abundance

Sea lamprey ( Petromyzon marinus ) is an invasive species that is a significant source of mortality for populations of valued fish species across the North American Great Lakes. Large annual control programs are needed to reduce the species' impacts; however, the number of successfully spawning adults cannot currently be accurately assessed. In this study, effective breeding size ( N b ) and the minimum number of spawning adults ( N s ) were estimated for larval cohorts from 17 tributaries across all five Great Lakes using single nucleotide polymorphisms (SNP) genotyped via RAD-capture sequencing. Reconstructed larval pedigrees showed substantial variability in the size and number of full- and half-sibling groups, N b (<1–367), and N s (5–545) among streams. Generalized linear models examining the effects of stream environmental characteristics and aspects of sampling regimes on N b and N s estimates identified sample size, the number of sampling sites, and drainage area as important factors predicting N b and N s . Correlations between N b , N s , and capture–mark–recapture estimates of adult census size ( N c ) increased when streams with small sample sizes ( n < 50) were removed. Results collectively indicate that parameters estimated from genetic data can provide valuable information on spawning adults in a river system, especially if sampling regimes are standardized and physical stream covariates are included.

Ecology and Evolution↗
USGS2023

Alternative measures of trait–niche relationships: A test on dispersal traits in saproxylic beetles

Functional trait approaches are common in ecology, but a lack of clear hypotheses on how traits relate to environmental gradients (i.e., trait–niche relationships) often makes uncovering mechanisms difficult. Furthermore, measures of community functional structure differ in their implications, yet inferences are seldom compared among metrics. Community-weighted mean trait values (CWMs), a common measure, are largely driven by the most common species and thus do not reflect community-wide trait–niche relationships per se. Alternatively, trait–niche relationships can be estimated across a larger group of species using hierarchical joint species distribution models (JSDMs), quantified by a parameter Γ. We investigated how inferences about trait–niche relationships are affected by the choice of metric. Using deadwood-dependent (saproxylic) beetles in fragmented Finnish forests, we followed a protocol for investigating trait–niche relationships by (1) identifying environmental filters (climate, forest age, and deadwood volume), (2) relating these to an ecological function (dispersal ability), and (3) identifying traits related to this function (wing morphology). We tested 18 hypothesized dispersal relationships using both CWM and Γ estimates across these environmental gradients. CWMs were more likely than Γ to show support for trait–niche relationships. Up to 13% of species' realized niches were explained by dispersal traits, but the directions of effects were consistent with fewer than 11%–39% of our 18 trait–niche hypotheses (depending on the metric used). This highlights the difficulty in connecting morphological traits and ecological functions in insects, despite the clear conceptual link between landscape connectivity and flight-related traits. Caution is thus warranted in hypothesis development, particularly where apparent trait–function links are less clear. Inferences differ when CWMs versus Γ estimates are used, necessitating the choice of a metric that reflects study questions. CWMs help explain the effects of environmental gradients on community trait composition, whereas the effects of traits on species' niches are better estimated using hierarchical JSDMs.

Ecology and Evolution↗
USGS2014

Estimating migratory connectivity of birds when re-encounter probabilities are heterogeneous

Understanding the biology and conducting effective conservation of migratory species requires an understanding of migratory connectivity – the geographic linkages of populations between stages of the annual cycle. Unfortunately, for most species, we are lacking such information. The North American Bird Banding Laboratory (BBL) houses an extensive database of marking, recaptures and recoveries, and such data could provide migratory connectivity information for many species. To date, however, few species have been analyzed for migratory connectivity largely because heterogeneous re-encounter probabilities make interpretation problematic. We accounted for regional variation in re-encounter probabilities by borrowing information across species and by using effort covariates on recapture and recovery probabilities in a multistate capture–recapture and recovery model. The effort covariates were derived from recaptures and recoveries of species within the same regions. We estimated the migratory connectivity for three tern species breeding in North America and over-wintering in the tropics, common (Sterna hirundo), roseate (Sterna dougallii), and Caspian terns (Hydroprogne caspia). For western breeding terns, model-derived estimates of migratory connectivity differed considerably from those derived directly from the proportions of re-encounters. Conversely, for eastern breeding terns, estimates were merely refined by the inclusion of re-encounter probabilities. In general, eastern breeding terns were strongly connected to eastern South America, and western breeding terns were strongly linked to the more western parts of the nonbreeding range under both models. Through simulation, we found this approach is likely useful for many species in the BBL database, although precision improved with higher re-encounter probabilities and stronger migratory connectivity. We describe an approach to deal with the inherent biases in BBL banding and re-encounter data to demonstrate that this large dataset is a valuable source of information about the migratory connectivity of the birds of North America.

Ecology and Evolution↗
USGS2023

Factors influencing autumn–winter movements of midcontinent Mallards and consequences for harvest and habitat management

Annual phenology and distributions of migratory wildlife have been noticeably influenced by climate change, leading to concerns about sustainable populations. Recent studies exploring conditions influencing autumn migration departure have provided conflicting insights regarding factors influencing the movements of Mallards ( Anas platyrhynchos ), a popular game species. We determined factors affecting timing and magnitude of long-distance movements of 97 juvenile Mallards during autumn-winter across the midcontinent of North America marked with implanted transmitters in North and South Dakota, 2018–2019. Factors influencing variation in movement timing, along with direction and magnitudes, depended on type of movement (i.e., regional [25–310 km], initial migration, or subsequent migration movements [>310 km]). Photoperiod influenced probability of initiating all movements, although the effect was most influential for regional movements. Minimum temperature most influenced initial migration events (probability of movement increased 29% for each 1°C decrease); favorable winds also increased likelihood of initial migration events. Probability of subsequent migration events increased 80% for each 1 cm increase in depth of snow. Subsequent migration movements also were 2.0 times more likely to occur on weekend days, indicating disturbance from humans may influence movements. Migration distances increased 166 km for each 1°C reduction in minimum temperature. We also observed markedly different autumn-winter distributions of marked birds between years. Median locations during autumn-winter 2018–2019 were ~250 km farther north and ~300 km farther west during mid-December–January compared to the same time in 2019–2020. Concurrently, harvest rates for marked females and males were 10% and 26% during autumn-winter 2018–2019 and 26% and 31% during autumn-winter 2019–2020. Climate-related changes may result in increasingly variable autumn-winter distributions, with implications for wildlife recreationalists, conservation planners, and harvest managers.

Ecology and Evolution↗