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USGS2008

Modelling invasion for a habitat generalist and a specialist plant species

Predicting suitable habitat and the potential distribution of invasive species is a high priority for resource managers and systems ecologists. Most models are designed to identify habitat characteristics that define the ecological niche of a species with little consideration to individual species' traits. We tested five commonly used modelling methods on two invasive plant species, the habitat generalist Bromus tectorum and habitat specialist Tamarix chinensis, to compare model performances, evaluate predictability, and relate results to distribution traits associated with each species. Most of the tested models performed similarly for each species; however, the generalist species proved to be more difficult to predict than the specialist species. The highest area under the receiver-operating characteristic curve values with independent validation data sets of B. tectorum and T. chinensis was 0.503 and 0.885, respectively. Similarly, a confusion matrix for B. tectorum had the highest overall accuracy of 55%, while the overall accuracy for T. chinensis was 85%. Models for the generalist species had varying performances, poor evaluations, and inconsistent results. This may be a result of a generalist's capability to persist in a wide range of environmental conditions that are not easily defined by the data, independent variables or model design. Models for the specialist species had consistently strong performances, high evaluations, and similar results among different model applications. This is likely a consequence of the specialist's requirement for explicit environmental resources and ecological barriers that are easily defined by predictive models. Although defining new invaders as generalist or specialist species can be challenging, model performances and evaluations may provide valuable information on a species' potential invasiveness.

Diversity and Distributions↗

USGS2018

Submerged aquatic vegetation mapping in coastal Louisiana through development of a spatial likelihood occurrence (SLOO) model

Determining the spatial distribution of coastal foundation species is essential to accurately determine restoration goals, predict the ecological effects of climate change, and develop habitat management strategies. Mapping the distribution of submerged aquatic vegetation (SAV) species assemblages, which provide important habitat resource and ecological services in Louisiana, has been difficult due to the dynamic nature of SAV occurrence and the limited water clarity across much of the coast. Species distribution models (SDMs) link ecological conditions species occurrence across landscapes, and can predict the distribution of species across un-sampled or hard to sample areas and support the development of habitat maps. To predict SAV distribution in coastal Louisiana, a SDM was developed and projected across the landscape to create a spatial likelihood of occurrence (SLOO) model describing the probability of SAV presence in aquatic habitats. SAV presence and absence data were examined from over 500 field observations in relation to physical and hydrologic variables, including exposure, turbidity, water level, and salinity. A binary logistic regression model (p < 0.0001) identified three significant predictors of SAV presence: mean winter salinity, exposure, and turbidity. As each of these variables increased, the probability of SAV presence in the summer growing season decreased. The spatial application of this SDM helps to predict the likelihood of occurrence across the coastal landscape, creating a valuable tool to describe un-sampled SAV habitat and estimate future changes in habitat availability.

Louisiana↗

USGS2005

Nutritional condition of elk in rocky mountain national park

We tested the hypothesis that elk in Rocky Mountain National Park (RMNP) were at ecological carrying capacity by determining herd-specific levels of nutritional condition and fecundity. Ingesta-free body fat levels in adult cows that were lactating were 10.6% (s = 1.7; range = 6.2-15.4) and 7.7% (s = 0.5; range = 5.9-10.1) in November 2001 for the Horseshoe and Moraine Park herds, respectively. Cows that were not lactating were able to accrue significantly more body fat: 14.0% (s = 1.1; range = 7.7-19.3) and 11.5% (s = 0.8; range = 8.6-15.1) for the Horseshoe and Moraine Park herds, respectively. Cow elk lost most of their body fat over winter (April 2002 levels were 3.9% [s = 0.4] and 2.9% [s = 0.4] for the Horseshoe and Moraine Park herds, respectively). Nutritional condition indicated that both Horseshoe Park and Moraine Park elk were well below condition levels elk can achieve on very good-excellent nutrition (i.e., >15% body fat; Cook et al. 2004) and were comparable to other free-ranging elk populations. However, condition levels were higher than those expected at a "food-limited" carrying capacity, and a proportion of elk in each herd were able to achieve condition levels indicative of very good-excellent nutrition. Elk in RMNP are likely regulated and/or limited by a complex combination of density-independent (including significant heterogeneity in forage conditions across RMNP's landscape) and density-dependent processes, as condition levels contradict a simple density-dependent model of a population at ecological carrying capacity.

Western North American Naturalist↗

USGS2012

Ecology of zoonotic infectious diseases in bats: current knowledge and future directions

Bats are hosts to a range of zoonotic and potentially zoonotic pathogens. Human activities that increase exposure to bats will likely increase the opportunity for infections to spill over in the future. Ecological drivers of pathogen spillover and emergence in novel hosts, including humans, involve a complex mixture of processes, and understanding these complexities may aid in predicting spillover. In particular, only once the pathogen and host ecologies are known can the impacts of anthropogenic changes be fully appreciated. Cross-disciplinary approaches are required to understand how host and pathogen ecology interact. Bats differ from other sylvatic disease reservoirs because of their unique and diverse lifestyles, including their ability to fly, often highly gregarious social structures, long lifespans and low fecundity rates. We highlight how these traits may affect infection dynamics and how both host and pathogen traits may interact to affect infection dynamics. We identify key questions relating to the ecology of infectious diseases in bats and propose that a combination of field and laboratory studies are needed to create data-driven mechanistic models to elucidate those aspects of bat ecology that are most critical to the dynamics of emerging bat viruses. If commonalities can be found, then predicting the dynamics of newly emerging diseases may be possible. This modelling approach will be particularly important in scenarios when population surveillance data are unavailable and when it is unclear which aspects of host ecology are driving infection dynamics.

Zoonoses and Public Health↗

USGS2008

Understanding and predicting ecological dynamics: Are major surprises inevitable

Ecological surprises, substantial and unanticipated changes in the abundance of one or more species that result from previously unsuspected processes, are a common outcome of both experiments and observations in community and population ecology. Here, we give examples of such surprises along with the results of a survey of well-established field ecologists, most of whom have encountered one or more surprises over the course of their careers. Truly surprising results are common enough to require their consideration in any reasonable effort to characterize nature and manage natural resources. We classify surprises as dynamic-, pattern-, or intervention-based, and we speculate on the common processes that cause ecological systems to so often surprise us. A long-standing and still growing concern in the ecological literature is how best to make predictions of future population and community dynamics. Although most work on this subject involves statistical aspects of data analysis and modeling, the frequency and nature of ecological surprises imply that uncertainty cannot be easily tamed through improved analytical procedures, and that prudent management of both exploited and conserved communities will require precautionary and adaptive management approaches.

Ecology↗

USGS2025

Predicting invasiveness of freshwater fishes imported into North America: Regional differences in models and outcomes

Biological invasions driven by international trade heighten the urgency for development of invasion risk models, as the traits and parameters that consistently predict successful invasion remain unresolved. For four regions of North America that include parts of the United States and Canada (Sacramento-San Joaquin River Basins, Lower Colorado River Basin, Great Lakes Region, Mid-Atlantic Region), we construct and compare classification tree models to reveal robust predictors for the establishment and ecological impact stages of freshwater fish invasion. We subsequently apply the models to identify invasive fish species in trade and conduct pathway analyses to determine which trades (aquarium, biological supply, live bait, live food, water garden) and source continents pose the greatest risk to each region. Model results differed by invasion stage and region. Across regions, establishment models shared climate-related predictors including climate match and temperature tolerance. Three of the four impact models contained prior establishment success. The greatest number of species (548) were predicted to establish in the Sacramento-San Joaquin while the fewest (5) were predicted to establish in the Mid-Atlantic. Forty species were predicted to establish in multiple regions, five of which were also predicted to have high impact. The aquarium trade and Asia supplied the most species predicted to establish. Taken together, the results highlight region-specific models, indicating no universal model predicts invasion. Climate-related and prior establishment variables were most useful to risk assessments. The regional models, and identified high-risk pathways and potential invaders, could be applied to prevent future fish invasions in North America.

Laurentian Great Lakes Region, Lower Colorado Rive↗

USGS2021

At-sea feeding ecology of parasitic lampreys

This paper synthesizes information on the at-sea ecology of ten anadromous lampreys, with emphasis on trophic ecology. The at-sea ecology of these lampreys concerns the juvenile stage, in which growth is most rapid. Anadromous lampreys can be categorized into four groups, based on feeding modalities: 1) scavenger (Caspian lamprey, Caspiomyzon wagneri ); 2) parasite-predator (Pacific lamprey, Entosphenus tridentatus ); 3) predators (western river lamprey, Lampetra ayresii ; European river lamprey, L. fluviatilis ; Arctic lamprey, Lethenteron camtschaticum ; pouched lamprey, Geotria australis ; and Argentinian pouched lamprey, G. macrostoma ); and 4) parasites (sea lamprey, Petromyzon marinus ; Chilean lamprey, Mordacia lapicida ; and short-headed lamprey, M. mordax ). This paper discusses direct evidence for lamprey feeding ecology, as observed through lamprey-induced wounds on hosts and prey, and lamprey attachments on hosts and prey; and indirect evidence for feeding ecology, via analyses of fatty acids, stable isotopes, contaminants, and bioenergetics modelling. A part of the information presented on feeding ecology is from landlocked sea lamprey, and in some instances this information can be generalizable to anadromous populations. For most anadromous lampreys, but particularly for Southern Hemisphere taxa, little is known about their feeding ecology at sea. Duration of the trophic marine phase and habitat use are still subjects of debate. Species identified as lamprey hosts can be demersal or pelagic, possibly reflecting marine habitat preferences. To unlock understanding of the marine phase of anadromous lampreys, direct evidence of feeding ecology should be coupled with natural (i.e., biomarkers) and artificial (e.g., biologgers) markers to identify habitat use, movement patterns and dispersal.

Journal of Great Lakes Research↗

USGS2012

Application of empirical predictive modeling using conventional and alternative fecal indicator bacteria in eastern North Carolina waters

Coastal and estuarine waters are the site of intense anthropogenic influence with concomitant use for recreation and seafood harvesting. Therefore, coastal and estuarine water quality has a direct impact on human health. In eastern North Carolina (NC) there are over 240 recreational and 1025 shellfish harvesting water quality monitoring sites that are regularly assessed. Because of the large number of sites, sampling frequency is often only on a weekly basis. This frequency, along with an 18–24 h incubation time for fecal indicator bacteria (FIB) enumeration via culture-based methods, reduces the efficiency of the public notification process. In states like NC where beach monitoring resources are limited but historical data are plentiful, predictive models may offer an improvement for monitoring and notification by providing real-time FIB estimates. In this study, water samples were collected during 12 dry (n = 88) and 13 wet (n = 66) weather events at up to 10 sites. Statistical predictive models for Escherichiacoli (EC), enterococci (ENT), and members of the Bacteroidales group were created and subsequently validated. Our results showed that models for EC and ENT (adjusted R2 were 0.61 and 0.64, respectively) incorporated a range of antecedent rainfall, climate, and environmental variables. The most important variables for EC and ENT models were 5-day antecedent rainfall, dissolved oxygen, and salinity. These models successfully predicted FIB levels over a wide range of conditions with a 3% (EC model) and 9% (ENT model) overall error rate for recreational threshold values and a 0% (EC model) overall error rate for shellfish threshold values. Though modeling of members of the Bacteroidales group had less predictive ability (adjusted R 2 were 0.56 and 0.53 for fecal Bacteroides spp. and human Bacteroides spp., respectively), the modeling approach and testing provided information on Bacteroidales ecology. This is the first example of a set of successful statistical predictive models appropriate for assessment of both recreational and shellfish harvesting water quality in estuarine waters.

North Carolina↗

USGS2016

Predicting animal home-range structure and transitions using a multistate Ornstein-Uhlenbeck biased random walk

The home‐range concept is central in animal ecology and behavior, and numerous mechanistic models have been developed to understand home range formation and maintenance. These mechanistic models usually assume a single, contiguous home range. Here we describe and implement a simple home‐range model that can accommodate multiple home‐range centers, form complex shapes, allow discontinuities in use patterns, and infer how external and internal variables affect movement and use patterns. The model assumes individuals associate with two or more home‐range centers and move among them with some estimable probability. Movement in and around home‐range centers is governed by a two‐dimensional Ornstein‐Uhlenbeck process, while transitions between centers are modeled as a stochastic state‐switching process. We augmented this base model by introducing environmental and demographic covariates that modify transition probabilities between home‐range centers and can be estimated to provide insight into the movement process. We demonstrate the model using telemetry data from sea otters ( Enhydra lutris ) in California. The model was fit using a Bayesian Markov Chain Monte Carlo method, which estimated transition probabilities, as well as unique Ornstein‐Uhlenbeck diffusion and centralizing tendency parameters. Estimated parameters could then be used to simulate movement and space use that was virtually indistinguishable from real data. We used Deviance Information Criterion (DIC) scores to assess model fit and determined that both wind and reproductive status were predictive of transitions between home‐range centers. Females were less likely to move between home‐range centers on windy days, less likely to move between centers when tending pups, and much more likely to move between centers just after weaning a pup. These tendencies are predicted by theoretical movement rules but were not previously known and show that our model can extract meaningful behavioral insight from complex movement data.

Ecology↗

USGS2024

Integrated distance sampling models for simple point counts

Point counts (PCs) are widely used in biodiversity surveys but, despite numerous advantages, simple PCs suffer from several problems: detectability, and therefore abundance, is unknown; systematic spatiotemporal variation in detectability yields biased inferences, and unknown survey area prevents formal density estimation and scaling-up to the landscape level. We introduce integrated distance sampling (IDS) models that combine distance sampling (DS) with simple PC or detection/nondetection (DND) data to capitalize on the strengths and mitigate the weaknesses of each data type. Key to IDS models is the view of simple PC and DND data as aggregations of latent DS surveys that observe the same underlying density process. This enables the estimation of separate detection functions, along with distinct covariate effects, for all data types. Additional information from repeat or time-removal surveys, or variable survey duration, enables the separate estimation of the availability and perceptibility components of detectability with DS and PC data. IDS models reconcile spatial and temporal mismatches among data sets and solve the above-mentioned problems of simple PC and DND data. To fit IDS models, we provide JAGS code and the new “ IDS() ” function in the R package unmarked . Extant citizen-science data generally lack the information necessary to adjust for detection biases, but IDS models address this shortcoming, thus greatly extending the utility and reach of these data. In addition, they enable formal density estimation in hybrid designs, which efficiently combine DS with distance-free, point-based PC or DND surveys. We believe that IDS models have considerable scope in ecology, management, and monitoring.

Ecology↗

USGS2020

Zero or not? Causes and consequences of zero-flow stream gage readings

Streamflow observations can be used to understand, predict, and contextualize hydrologic, ecological, and biogeochemical processes and conditions in streams. Stream gages are point measurements along rivers where streamflow is measured, and are often used to infer upstream watershed‐scale processes. When stream gages read zero, this may indicate that the stream has dried at this location; however, zero‐flow readings can also be caused by a wide range of other factors. Our ability to identify whether or not a zero‐flow gage reading indicates a dry fluvial system has far reaching environmental implications. Incorrect identification and interpretation by the data user can lead to inaccurate hydrologic, ecological, and/or biogeochemical predictions from models and analyses. Here, we describe several causes of zero‐flow gage readings: frozen surface water, flow reversals, instrument error, and natural or human‐driven upstream source losses or bypass flow. For these examples, we discuss the implications of zero‐flow interpretations. We also highlight additional methods for determining flow presence, including direct observations, statistical methods, and hydrologic models, which can be applied to interpret causes of zero‐flow gage readings and implications for reach‐ and watershed‐scale dynamics. Such efforts are necessary to improve our ability to understand and predict surface flow activation, cessation, and connectivity across river networks. Developing this integrated understanding of the wide range of possible meanings of zero‐flows will only attain greater importance in a more variable and changing hydrologic climate.

WIREs Water↗

USGS2005

Multi-scale remote sensing of coral reefs

In this chapter we present how both direct and indirect remote sensing can be integrated to address two major coral reef applications - coral bleaching and assessment of biodiversity. This approach reflects the current non-linear integration of remote sensing for environmental assessment of coral reefs, resulting from a rapid increase in available sensors, processing methods and interdisciplinary collaborations (Andréfouët and Riegl, 2004). Moreover, this approach has greatly benefited from recent collaborations of once independent investigations (e.g., benthic ecology, remote sensing, and numerical modeling).

Florida↗

USGS2018

Assessment of potential risks from renewable energy development and other anthropogenic factors to wintering Golden Eagles in the western United States

Wind and other energy development are expanding rapidly and on an unprecedented scale within the range of the Golden Eagle ( Aquila chrysaetos ) while other anthropogenic-related changes, wildfires, invasive plants, drought, and climate change are altering or destroying native habitats occupied by Golden Eagles. However, the potential effects of these factors on North American Golden Eagle populations are largely unknown and the most recent evidence indicates that the population in the western United States is declining slightly. Impediments to evaluating the potential effects of energy development projects on wintering Golden Eagles include issues of scale and a paucity of available information about eagle winter use areas and ecology. We applied a predictive model of eagle winter distribution developed for Idaho and Montana, to Idaho, Utah, Nevada and eastern Oregon to help identify potential wintering areas and identify risks that occur in those areas. The model identifies ~40% of the four state study area as potentially suitable eagle winter habitat and provides a basis for spatial assessment of possible risk factors to eagles wintering there. We used eBird and Christmas Bird Count citizen science datasets for an independent evaluation of the accuracy of our predictive distribution model. The model was robust, accurately predicting the presence of wintering Golden Eagles significantly more often than expected. We used digital environmental datasets (layers) of potential risk factors, in conjunction with model predicted eagle distribution, to better understand and estimate the extent of risks to the wintering eagle population in the study area. These layers represent available data for some of the factors previously identified as risks in the landscape to wintering Golden Eagles. The majority of predicted eagle wintering areas occurred where there was little habitat fragmentation (<10%). All predicted winter areas contained at least one potential risk factor (e.g., potential for energy development); 39.4% of predicted winter areas contained at least two known risk factors. The greatest number of risks often occurred where the human footprint was highest and where eagles were less likely to occur during winter. Our results can be used to help prioritize field surveys for identifying important Golden Eagle winter areas in the western United States and determine potential locations where energy development is least likely to have negative effects on wintering eagles. Survey efforts can be allocated in consideration of management and conservation objectives based on predicted habitat suitability and risk factors. For example, surveys for areas of high suitability and low risk can identify places to focus management for conservation of eagle winter areas. Further, sites proposed for wind energy development could be reviewed initially based on model predicted eagle wintering areas and then surveyed to determine if permitting for development is appropriate.

Book chapter↗

USGS2014

Sustainability of the Lake Superior fish community: Interactions in a food web context

The restoration and rehabilitation of the native fish communities is a long-term goal for the Laurentian Great Lakes. In Lake Superior, the ongoing restoration of the native lake trout populations is now regarded as one of the major success stories in fisheries management. However, populations of the deepwater morphotype (siscowet lake trout) have increased much more substantially than those of the nearshore morphotype (lean lake trout), and the ecosystem now contains an assemblage of exotic species such as sea lamprey, rainbow smelt, and Pacific salmon (chinook, coho, and steelhead). Those species play an important role in defining the constraints and opportunities for ecosystem management. We combined an equilibrium mass balance model (Ecopath) with a dynamic food web model (Ecosim) to evaluate the ecological consequences of future alternative management strategies and the interaction of two different sets of life history characteristics for fishes at the top of the food web. Relatively rapid turnover rates occur among the exotic forage fish, rainbow smelt, and its primary predators, exotic Pacific salmonids. Slower turnover rates occur among the native lake trout and burbot and their primary prey—lake herring, smelt, deepwater cisco, and sculpins. The abundance of forage fish is a key constraint for all salmonids in Lake Superior. Smelt and Mysis play a prominent role in sustaining the current trophic structure. Competition between the native lake trout and the exotic salmonids is asymmetric. Reductions in the salmon population yield only a modest benefit for the stocks of lake trout, whereas increased fishing of lake trout produces substantial potential increases in the yields of Pacific salmon to recreational fisheries. The deepwater or siscowet morphotype of lake trout has become very abundant. Although it plays a major role in the structure of the food web it offers little potential for the restoration of a valuable commercial or recreational fishery. Even if a combination of strong management actions is implemented, the populations of lean (nearshore) lake trout cannot be restored to pre-fishery and pre-lamprey levels. Thus, management strategy must accept the ecological constraints due in part to the presence of exotics and choose alternatives that sustain public interest in the resources while continuing the gradual progress toward restoration.

Ecosystems↗

USGS2015

Climate change impacts on ecosystems and ecosystem services in the United States: Process and prospects for sustained assessment

The third United States National Climate Assessment emphasized an evaluation of not just the impacts of climate change on species and ecosystems, but also the impacts of climate change on the benefits that people derive from nature, known as ecosystem services. The ecosystems, biodiversity, and ecosystem services component of the assessment largely drew upon the findings of a transdisciplinary workshop aimed at developing technical input for the assessment, involving participants from diverse sectors. A small author team distilled and synthesized this and hundreds of other technical input to develop the key findings of the assessment. The process of developing and ranking key findings hinged on identifying impacts that had particular, demonstrable effects on the U.S. public via changes in national ecosystem services. Findings showed that ecosystem services are threatened by the impacts of climate change on water supplies, species distributions and phenology, as well as multiple assaults on ecosystem integrity that, when compounded by climate change, reduce the capacity of ecosystems to buffer against extreme events. As ecosystems change, such benefits as water sustainability and protection from storms that are afforded by intact ecosystems are projected to decline across the continent due to climate change. An ongoing, sustained assessment that focuses on the co-production of actionable climate science will allow scientists from a range of disciplines to ascertain the capability of their forecasting models to project environmental and ecological change and link it to ecosystem services; additionally, an iterative process of evaluation, development of management strategies, monitoring, and reevaluation will increase the applicability and usability of the science by the U.S. public.

Climatic Change↗

USGS2015

Rapid isolation of microsatellite DNAs and identification of polymorphic mitochondrial DNA regions in the fish rotan (Perccottus glenii) invading European Russia

Human-mediated translocations and subsequent large-scale colonization by the invasive fish rotan (Perccottus glenii Dybowski, 1877; Perciformes, Odontobutidae), also known as Amur or Chinese sleeper, has resulted in dramatic transformations of small lentic ecosystems. However, no detailed genetic information exists on population structure, levels of effective movement, or relatedness among geographic populations of P. glenii within the European part of the range. We used massively parallel genomic DNA shotgun sequencing on the semiconductor-based Ion Torrent Personal Genome Machine (PGM) sequencing platform to identify nuclear microsatellite and mitochondrial DNA sequences in P. glenii from European Russia. Here we describe the characterization of nine nuclear microsatellite loci, ascertain levels of allelic diversity, heterozygosity, and demographic status of P. glenii collected from Ilev, Russia, one of several initial introduction points in European Russia. In addition, we mapped sequence reads to the complete P. glenii mitochondrial DNA sequence to identify polymorphic regions. Nuclear microsatellite markers developed for P. glenii yielded sufficient genetic diversity to: (1) produce unique multilocus genotypes; (2) elucidate structure among geographic populations; and (3) provide unique perspectives for analysis of population sizes and historical demographics. Among 4.9 million filtered P. glenii Ion Torrent PGM sequence reads, 11,304 mapped to the mitochondrial genome (NC_020350). This resulted in 100 % coverage of this genome to a mean coverage depth of 102X. A total of 130 variable sites were observed between the publicly available genome from China and the studied composite mitochondrial genome. Among these, 82 were diagnostic and monomorphic between the mitochondrial genomes and distributed among 15 genome regions. The polymorphic sites (N = 48) were distributed among 11 mitochondrial genome regions. Our results also indicate that sequence reads generated from two three-hour runs on the Ion Torrent PGM can generate a sufficient number of nuclear and mitochondrial markers to improve understanding of the evolutionary and ecological dynamics of non-model and in particular, invasive species.

European Russia↗

USGS2024

A fire-use decision model to improve the United States’ wildfire management and support climate change adaptation

The US faces multiple challenges in facilitating the safe, effective, and proactive use of fire as a landscape management tool. This intentional fire use exposes deeply ingrained communication challenges and distinct but overlapping strategies of prescribed fire, cultural burning, and managed wildfire. We argue for a new conceptual model that is organized around ecological conditions, capacity to act, and motivation to use fire and can integrate and expand intentional fire use as a tool. This result emerges from more considered collaboration and communication of values and needs to address the negative consequences of contemporary fire use. When applied as a communication and translation tool, there is potential to lower barriers to faster and more successful collaboration among stakeholders. Such improvements are a vital part of strategies to address climate adaptation, wildfire mitigation, and the well-being of ecosystems.

Cell Reports Sustainability↗

USGS2023

A 1300-year microfaunal record from the Beaufort Sea shelf indicates exceptional climate-related environmental changes over the last two centuries

The environments of Arctic Ocean nearshore areas experience high intra- and inter-annual variability, making it difficult to evaluate the impact of anthropogenic warming. However, a sediment record from the southern Canadian Beaufort Sea allowed us to reconstruct the impacts of climate and environmental changes over the last 1300 years along the northern Yukon coast, Canada. The coring site (PG2303; 69.513°N, 138.895°W; water depth 32 m) is located in the Herschel Basin, where high sedimentation rates (0.1–0.5 cm a −1 ) allowed analyses at sub-centennial to decadal resolutions. Benthic foraminiferal, ostracod, and tintinnid assemblages, as well as the stable isotope composition of the foraminifera Elphidium clavatum and Cassidulina reniforme were used as paleoclimatic and ecological indicators, while the age model was based on the combined radiometric data of 14 C, 210 Pb and 137 Cs . From ca 700 to 1050 CE, our data suggest penetration of offshore shelf-break waters inferred by the dominance of C. reniforme followed by the relatively abundant Triloculina trihedra in the foraminiferal assemblages as both species are associated with stable saline conditions. Afterwards, the occurrence of ostracods Kotoracythere arctoborealis and Normanicythere leioderma suggests influx of Pacific-sourced waters until ca. 1150 CE. From ∼1150–1650 CE, persistent frigid waters, limited sediment supply, and low abundances of microfossils suggest cold conditions with pervasive annual sea-ice cover that may have restricted upwelling of oceanic waters. After ∼1800 CE, the co-occurrence of Tintinnopsis fimbriata and bacterial/complex organic carbon feeder foraminifera ( Quinqueloculina stalkeri , Textularia earlandi and Stetsonia horvathi ), suggest an increased influence of freshwater rich in particulate organic matter, which may be related to the spreading of the Mackenzie River plume and/or increased coastal permafrost erosion during longer ice-free seasons. Based on these proxy data, the shift at ∼1800 CE marks the onset of regional warming, which further intensified after ∼1955 CE, likely in response to the anthropogenic forcing.

Alaska, Yukon↗