Paleoceanograpic changes on the Farallon Escarpment off central California during the last 16,000 years
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Radiocarbon age-offsets in an arctic lake reveal the long-term response of permafrost carbon to climate change
Continued warming of the Arctic may cause permafrost to thaw and speed the decomposition of large stores of soil organic carbon (OC), thereby accentuating global warming. However, it is unclear if recent warming has raised the current rates of permafrost OC release to anomalous levels or to what extent soil carbon release is sensitive to climate forcing. Here we use a time series of radiocarbon age-offsets ( 14 C) between the bulk lake sediment and plant macrofossils deposited in an arctic lake as an archive for soil and permafrost OC release over the last 14,500 years. The lake traps and archives OC imported from the watershed and allows us to test whether prior warming events stimulated old carbon release and heightened age-offsets. Today, the age-offset (2 ka; thousand of calibrated years before A.D. 1950) and the depositional rate of ancient OC from the watershed into the lake are relatively low and similar to those during the Younger Dryas cold interval (occurring 12.9–11.7 ka). In contrast, age-offsets were higher (3.0–5.0 ka) when summer air temperatures were warmer than present during the Holocene Thermal Maximum (11.7–9.0 ka) and Bølling-Allerød periods (14.5–12.9 ka). During these warm times, permafrost thaw contributed to ancient OC depositional rates that were ~10 times greater than today. Although permafrost OC was vulnerable to climate warming in the past, we suggest surface soil organic horizons and peat are presently limiting summer thaw and carbon release. As a result, the temperature threshold to trigger widespread permafrost OC release is higher than during previous warming events.
Alaska↗
Role of ground ice dynamics and ecological feedbacks in recent ice wedge degradation and stabilization
Ground ice is abundant in the upper permafrost throughout the Arctic and fundamentally affects terrain responses to climate warming. Ice wedges, which form near the surface and are the dominant type of massive ice in the Arctic, are particularly vulnerable to warming. Yet processes controlling ice wedge degradation and stabilization are poorly understood. Here we quantified ice wedge volume and degradation rates, compared ground ice characteristics and thermal regimes across a sequence of five degradation and stabilization stages and evaluated biophysical feedbacks controlling permafrost stability near Prudhoe Bay, Alaska. Mean ice wedge volume in the top 3 m of permafrost was 21%. Imagery from 1949 to 2012 showed thermokarst extent (area of water-filled troughs) was relatively small from 1949 (0.9%) to 1988 (1.5%), abruptly increased by 2004 (6.3%) and increased slightly by 2012 (7.5%). Mean annual surface temperatures varied by 4.9°C among degradation and stabilization stages and by 9.9°C from polygon center to deep lake bottom. Mean thicknesses of the active layer, ice-poor transient layer, ice-rich intermediate layer, thermokarst cave ice, and wedge ice varied substantially among stages. In early stages, thaw settlement caused water to impound in thermokarst troughs, creating positive feedbacks that increased net radiation, soil heat flux, and soil temperatures. Plant growth and organic matter accumulation in the degraded troughs provided negative feedbacks that allowed ground ice to aggrade and heave the surface, thus reducing surface water depth and soil temperatures in later stages. The ground ice dynamics and ecological feedbacks greatly complicate efforts to assess permafrost responses to climate change.
Journal of Geophysical Research F: Earth Surface↗
Sea level driven marsh expansion in a coupled model of marsh erosion and migration
Coastal wetlands are among the most valuable ecosystems on Earth, where ecosystem services such as flood protection depend nonlinearly on wetland size and are threatened by sea level rise and coastal development. Here we propose a simple model of marsh migration into adjacent uplands and couple it with existing models of seaward edge erosion and vertical soil accretion to explore how ecosystem connectivity influences marsh size and response to sea level rise. We find that marsh loss is nearly inevitable where topographic and anthropogenic barriers limit migration. Where unconstrained by barriers, however, rates of marsh migration are much more sensitive to accelerated sea level rise than rates of edge erosion. This behavior suggests a counterintuitive, natural tendency for marsh expansion with sea level rise and emphasizes the disparity between coastal response to climate change with and without human intervention.
Geophysical Research Letters↗
Landform features and seasonal precipitation predict shallow groundwater influence on temperature in headwater streams
Headwater stream responses to climate change will depend in part on groundwater‐surface water exchanges. We used linear modeling techniques to partition likely effects of shallow groundwater seepage and air temperature on stream temperatures for 79 sites in nine focal watersheds using hourly air and water temperature measurements collected during summer months from 2012 to 2015 in Shenandoah National Park, Virginia, USA. Shallow groundwater effects exhibited more variation within watersheds than between them, indicating the importance of reach‐scale assessments and the limited capacity to extrapolate upstream groundwater influences from downstream measurements. Boosted regression tree (BRT) models revealed intricate interactions among geomorphological landform features (stream slope, elevation, network length, contributing area, and channel confinement) and seasonal precipitation patterns (winter, spring, and summer months) that together were robust predictors of spatial and temporal variation in groundwater influence on stream temperatures. The final BRT model performed well for training data and cross‐validated samples (correlation = 0.984 and 0.760, respectively). Geomorphological and precipitation predictors of groundwater influence varied in their importance between watersheds, suggesting differences in spatial and temporal controls of recharge dynamics and the depth of the groundwater source. We demonstrate an application of the final BRT model to predict groundwater effects from landform and precipitation covariates at 1075 new sites distributed at 100 m increments within focal watersheds. Our study provides a framework to estimate effects of groundwater seepage on stream temperature in unsampled locations. We discuss applications for climate change research to account for groundwater‐surface water interactions when projecting future thermal thresholds for stream biota.
Virginia↗
Geographic variation in the intensity of warming and phenological mismatch between Arctic shorebirds and invertebrates
Responses to climate change can vary across functional groups and trophic levels, leading to a temporal decoupling of trophic interactions or ‘phenological mismatches.’ Despite a growing number of single-species studies that identified phenological mismatches as a nearly universal consequence of climate change, we have a limited understanding of the spatial variation in the intensity of this phenomenon nor what influences this variation. In this study, we tested for geographic patterns in phenological mismatches between six species of shorebirds and their invertebrate prey at ten sites spread across ~13º latitude and ~84º longitude in the Arctic over three years. At each site, we quantified the phenological mismatch between shorebirds and their invertebrate prey at: 1) an individual nest level, as the difference in days between the seasonal peak in food and the peak demand by chicks, and 2) a population level, as the overlapped area under fitted curves for total daily biomass of invertebrates and dates of the peak demand by chicks. We tested whether the intensity of past climatic change observed at each site corresponded with the extent of phenological mismatch and used Structural Equation Modeling to test for causal relationships among: 1) environmental factors, including geographic location and current climatic conditions, 2) the timing of invertebrate emergence and the breeding phenology of shorebirds, and 3) the phenological mismatch between the two trophic levels. The extent of phenological mismatch varied more among different sites than among different species within each site. A greater extent of phenological mismatch at both the individual-nest and population-levels coincided with changes in the timing of snowmelt as well as the potential dissociation of long-term snow phenology from changes in temperature. The timing of snowmelt also affected the shape of the food and demand curves, which determined the extent of phenological mismatch at the population level. Finally, we found larger mismatches at more easterly longitudes, which may be affecting the population dynamics of shorebirds, as two of our study species show regional population declines in only the eastern part of their range. This suggests that phenological mismatches may be resulting in demographic consequences for arctic-nesting birds.
Alaska↗
Estimating thermal performance curves from repeated field observations
Estimating thermal performance of organisms is critical for understanding population distributions and dynamics and predicting responses to climate change. Typically, performance curves are estimated using laboratory studies to isolate temperature effects, but other abiotic and biotic factors influence temperature-performance relationships in nature reducing these models' predictive ability. We present a model for estimating thermal performance curves from repeated field observations that includes environmental and individual variation. We fit the model in a Bayesian framework using MCMC sampling, which allowed for estimation of unobserved latent growth while propagating uncertainty. Fitting the model to simulated data varying in sampling design and parameter values demonstrated that the parameter estimates were accurate, precise, and unbiased. Fitting the model to individual growth data from wild trout revealed high out-of-sample predictive ability relative to laboratory-derived models, which produced more biased predictions for field performance. The field-based estimates of thermal maxima were lower than those based on laboratory studies. Under warming temperature scenarios, field-derived performance models predicted stronger declines in body size than laboratory-derived models, suggesting that laboratory-based models may underestimate climate change effects. The presented model estimates true, realized field performance, avoiding assumptions required for applying laboratory-based models to field performance, which should improve estimates of performance under climate change and advance thermal ecology.
Ecology↗
Cryptic ice wedge networks in Holocene peat, Yukon-Kuskokwim Delta, Alaska
The Yukon-Kuskokwim Delta (YKD), covering ~75,000 km 2 of Alaska's discontinuous permafrost zone, has a historic (1902–2023) mean annual air temperature of ~−1°C and was previously thought to lack ice wedge networks. However, our recent investigations near Bethel, Alaska, revealed numerous near-surface ice wedges. Using 20 cm resolution aerial orthoimagery from 2018, we identified ~50 linear km of ice wedge troughs in a 60 km 2 study area. Fieldwork in 2023 and 2024 confirmed ice wedges up to ~1.5 m wide and ~2.5 m in vertical extent, situated on average 0.9 m below the tundra surface ( n = 29). Ground-penetrating radar (GPR) detected additional ice wedges beyond those visible in the remote sensing imagery, suggesting an underestimation of their true abundance. Coring of polygonal centers revealed late-Quaternary deposits, including thick early Holocene peat, late-Pleistocene ice-rich silts (reworked Yedoma), charcoal layers from tundra fires, and the Aniakchak CFE II tephra (~3600 cal yrs BP). Stable water isotopes from Bethel's wedge ice (mean δ 18 O = −15.7 ‰, δ 2 H = −113.1 ‰) indicate a relatively enriched signature compared to other Holocene ice wedges in Alaska, likely due to warmer temperatures and maritime influences. Expanding our mapping across the YKD using high-resolution satellite imagery from 2012 to 2024, we estimate that the Holocene ice wedge zone encompasses ~30% of the YKD tundra region. Our findings demonstrate that ice wedge networks are more widespread across the YKD than previously recognized, emphasizing both the resilience and vulnerability of the region's warm, ice-rich permafrost. These insights are crucial for understanding permafrost responses to climate change and assessing agricultural potential and development in the region.
Alaska↗
Analysis of the surface hydrology in a regional climate model
This paper discusses the surface hydrology of a multi‐year simulation of present day climate over the United States (US) conducted with a regional climate model (RegCM) nested within a general circulation model (GCM). The RegCM, which is run with a 60 km gridpoint spacing is interactively coupled with a state‐of‐the‐art surface physics package that includes full surface hydrology calculations (the Biosphere‐Atmosphere Transfer Scheme or BATS). The hydrologic budgets of ten regional drainage basins in the US are analysed. Model results are compared with available observations and with results from previous modelling experiments to evaluate the feasibility of using nested RegCM/GCM models for hydrology studies. In our experiment, the model captures the basic seasonality of the basin hydrologic budgets, although the simulated precipitation amounts are too high over the western US and too low over the eastern US. As a result, runoff, snow cover and soil water content are underestimated over the eastern US basins, while evaporation and runoff are overestimated in some of the western US basins. Topographically induced characteristics of precipitation, snow cover and runoff are well simulated over the mountainous western regions. Also well captured is the inter‐basin variation of hydrologic budgets which occurs in response to different climatic settings. The springtime snowmelt and peak runoff season generally occurs in the model earlier in the year than is observed. Although our work indicates that the coupled regional modelling system can be useful in applications to hydrological studies, results from this experiment indicate that better accuracy in the simulation of regional climatic variables and more detailed representation of some hydrologic processes would be required before the coupled modelling system could be used to provide accurate assessments of hydrologic responses to climate change.
Quarterly Journal of the Royal Meteorological Soci↗
Culverts delay upstream and downstream migrations of river herring (Alosa spp.)
Alewife ( Alosa pseudoharengus ) and blueback herring ( Alosa aestivalis ) are iteroparous anadromous fish found throughout the East Coast of North America. The phenology of anadromous fish migrations is important for fitness, and the duration of spawning migrations has been compressed in recent years in response to climate change. Anthropogenic barriers to movement, such as dams and culverts at road-stream crossings, can further disrupt migration phenology by delaying movement and increasing predation risk. We used passive integrated transponder (PIT) telemetry to quantify upstream and downstream migratory delay at five road-stream-crossing culverts on the Herring River (MA, USA). Groundspeeds were reduced at all culverts in both directions, confirming that the culverts impede movement despite high passage proportions. The cumulative delay of the culverts on the upstream migration was sufficient to more than double the amount of time required to traverse the river if the culverts had been absent. Furthermore, the presence of snapping turtles ( Chelydra serpentina ) ambushing river herring within one of the culverts resulted in reduced passage rates beyond the reduction in movement caused by the physical structure itself. This highlights that physical barriers can create cascading ecological consequences and the importance of taking a holistic approach to understanding barrier effects.
Massachusetts↗
Looking beyond wildlife: Using remote cameras to evaluate accuracy of gridded snow data
The use of remote cameras is widespread in wildlife ecology, yet few examples exist of their utility for collecting environmental data. We used a novel camera trap method to evaluate the accuracy of gridded snow data in a mountainous region of the northeastern US. We were specifically interested in assessing (1) how snow depth observations from remote cameras compare with gridded climate data, (2) the sources of error associated with the gridded data and (3) the influence of spatial sampling on bias. We compared daily observations recorded by remote cameras with Snow Data Assimilation System (SNODAS ) gridded predictions using data from three winters (2014–2016). Snow depth observations were correlated with SNODAS predictions for sites ( R 2 = 0.20) and regions ( R 2 = 0.16), yet we detected factors associated with SNODAS bias at both scales. Specifically, SNODAS underpredicted depths at high elevations, at sites with higher solar radiation, and within conifer‐dominated forest. Depths were most underpredicted at highest elevations, up to 44 and 26 cm on average at the site and region scales, respectively. Bias was greatest when predictions were lowest, occasionally predicting snow absence when depths were >100 cm at camera sites. We also detected breakdowns in accuracy when certain environmental conditions varied within the 1 km 2 SNODAS grid cells. For example, underprediction was greatest when the solar radiation values of camera stations increased relative to the mean of the SNODAS grid cells. This relationship was most prominent in mountainous regions, suggesting that factors which influence solar radiation (e.g. topographic complexity) contribute to SNODAS inaccuracy. We caution using gridded snow data for ecological studies when bias is unknown. We suggest increased sampling to adjust for errors associated with gridded data products that arise from factors, such as forest cover and topographic variability. Increasing resolution and accuracy of climate data will improve predictions of species’ responses to climate change.
New Hampshire, Vermont↗
Stochastic variation in avian survival rates: Life-history predictions, population consequences, and the potential responses to human perturbations and climate change
Stochastic variation in survival rates is expected to decrease long-term population growth rates. This expectation influences both life-history theory and the conservation of species. From this expectation, Pfister ( 1998 ) developed the important life-history prediction that natural selection will have minimized variability in those elements of the annual life cycle (such as adult survival rate) with high sensitivity. This prediction has not been rigorously evaluated for bird populations, in part due to statistical difficulties related to variance estimation. I here overcome these difficulties, and in an analysis of 62 populations, I confirm her prediction by showing a negative relationship between the proportional sensitivity (elasticity) of adult survival and the proportional variance (CV) of adult survival. However, several species deviated significantly from this expectation, with more process variance in survival than predicted. For instance, projecting the magnitude of process variance in annual survival for American redstarts ( Setophaga ruticilla ) for 25 years resulted in a 44% decline in abundance without assuming any change in mean survival rate. For most of these species with high process variance, recent changes in harvest, habitats, or changes in climate patterns are the likely sources of environmental variability causing this variability in survival. Because of climate change, environmental variability is increasing on regional and global scales, which is expected to increase stochasticity in vital rates of species. Increased stochasticity in survival will depress population growth rates, and this result will magnify the conservation challenges we face.
Book chapter↗
Assessment and Mmanagement of North American horseshoe crab populations, with emphasis on a multispecies framework for Delaware Bay, U.S.A. populations: Chapter 24
The horseshoe crab fishery on the US Atlantic coast represents a compelling fishery management story for many reasons, including ecological complexity, health and human safety ramifications, and socio-economic conflicts. Knowledge of stock status and assessment and monitoring capabilities for the species have increased greatly in the last 15 years and permitted managers to make more informed harvest recommendations. Incorporating the bioenergetics needs of migratory shorebirds, which feed on horseshoe crab eggs, into the management framework for horseshoe crabs was identified as a goal, particularly in the Delaware Bay region where the birds and horseshoe crabs exhibit an important ecological interaction. In response, significant effort was invested in studying the population dynamics, migration ecology, and the ecologic relationship of a key migratory shorebird, the Red Knot, to horseshoe crabs. A suite of models was developed that linked Red Knot populations to horseshoe crab populations through a mass gain function where female spawning crab abundance determined what proportion of the migrating Red Knot population reached a critical body mass threshold. These models were incorporated in an adaptive management framework wherein optimal harvest decisions for horseshoe crab are recommended based on several resource-based and value-based variables and thresholds. The current adaptive framework represents a true multispecies management effort where additional data over time are employed to improve the predictive models and reduce parametric uncertainty. The possibility of increasing phenologic asynchrony between the two taxa in response to climate change presents a potential challenge to their ecologic interaction in Delaware Bay.
Book chapter↗
Phenological adjustment in arctic bird species: relative importance of snow melt and ecological factors
Previous studies have documented advancement in clutch initiation dates (CIDs) in response to climate change, most notably for temperate-breeding passerines. Despite accelerated climate change in the Arctic, few studies have examined nest phenology shifts in arctic breeding species. We investigated whether CIDs have advanced for the most abundant breeding shorebird and passerine species at a long-term monitoring site in arctic Alaska. We pooled data from three additional nearby sites to determine the explanatory power of snow melt and ecological variables (predator abundance, green-up) on changes in breeding phenology. As predicted, all species (semipalmated sandpiper, Calidris pusilla , pectoral sandpiper, Calidris melanotos , red-necked phalarope, Phalaropus lobatus , red phalarope, Phalaropus fulicarius , Lapland longspur, Calcarius lapponicus ) exhibited advanced CIDs ranging from 0.40 to 0.80 days/year over 9 years. Timing of snow melt was the most important variable in explaining clutch initiation advancement (“climate/snow hypothesis”) for four of the five species, while green-up was a much less important explanatory factor. We found no evidence that high predator abundances led to earlier laying dates (“predator/re-nest hypothesis”). Our results support previous arctic studies in that climate change in the cryosphere will have a strong impact on nesting phenology although factors explaining changes in nest phenology are not necessarily uniform across the entire Arctic. Our results suggest some arctic-breeding shorebird and passerine species are altering their breeding phenology to initiate nesting earlier enabling them to, at least temporarily, avoid the negative consequences of a trophic mismatch.
Alaska↗
Local environmental conditions structured discrete fish assemblages in Arctic lagoons
Rapid changes in sea ice extent and changes in freshwater inputs from land are rapidly changing the nature of Arctic estuarine ecosystems. In the Beaufort Sea, these nearshore habitats are known for their high productivity and mix of marine resident and diadromous fishes that have great subsistence value for Indigenous communities. There is, however, a lack of information on the spatial variation among Arctic nearshore fish communities as related to environmental drivers. In summers of 2017–2019, we sampled fishes in four estuarine ecosystems to assess community composition and relate fish abundance to temperature, salinity, and wind conditions. We found fish communities were heterogeneous over larger spatial extents with rivers forming fresh estuarine plumes that supported diadromous species (e.g., broad whitefish Coregonus nasus ), while lagoons with reduced freshwater input and higher salinities were associated with marine species (e.g., saffron cod Eleginus gracilis ). West–East directional winds accounted for up to 66% of the community variation, indicating importance of the wind-driven balance between fresh and marine water masses. Salinity and temperature accounted for up to 54% and 37% of the variation among lagoon communities, respectively. Recent sea ice declines provide more opportunity for wind to influence oceanographic conditions and biological communities. Current subsistence practices, future commercial fishing opportunities, and on-going oil and gas activities benefit from a better understanding of current fish community distributions. This work provides important data on fish spatial distributions and community composition, providing a basis for fish community response to changing climatic conditions and anthropogenic use.
Polar Biology↗
Potential increase in floods in California's Sierra Nevada under future climate projections
California’s mountainous topography, exposure to occasional heavily moisture-laden storm systems, and varied communities and infrastructures in low lying areas make it highly vulnerable to floods. An important question facing the state—in terms of protecting the public and formulating water management responses to climate change—is “how might future climate changes affect flood characteristics in California?” To help address this, we simulate floods on the western slopes of the Sierra Nevada Mountains, the state’s primary catchment, based on downscaled daily precipitation and temperature projections from three General Circulation Models (GCMs). These climate projections are fed into the Variable Infiltration Capacity (VIC) hydrologic model, and the VIC-simulated streamflows and hydrologic conditions, from historical and from projected climate change runs, allow us to evaluate possible changes in annual maximum 3-day flood magnitudes and frequencies of floods. By the end of the 21st Century, all projections yield larger-than-historical floods, for both the Northern Sierra Nevada (NSN) and for the Southern Sierra Nevada (SSN). The increases in flood magnitude are statistically significant (at p <= 0.01) for all the three GCMs in the period 2051–2099. The frequency of flood events above selected historical thresholds also increases under projections from CNRM CM3 and NCAR PCM1 climate models, while under the third scenario, GFDL CM2.1, frequencies remain constant or decline slightly, owing to an overall drying trend. These increases appear to derive jointly from increases in heavy precipitation amount, storm frequencies, and days with more precipitation falling as rain and less as snow. Increases in antecedent winter soil moisture also play a role in some areas. Thus, a complex, as-yet unpredictable interplay of several different climatic influences threatens to cause increased flood hazards in California’s complex western Sierra landscapes.
California↗
The response of Lake Tahoe to climate change
Meteorology is the driving force for lake internal heating, cooling, mixing, and circulation. Thus continued global warming will affect the lake thermal properties, water level, internal nutrient loading, nutrient cycling, food-web characteristics, fish-habitat, aquatic ecosystem, and other important features of lake limnology. Using a 1-D numerical model - the Lake Clarity Model (LCM) - together with the down-scaled climatic data of the two emissions scenarios (B1 and A2) of the Geophysical Fluid Dynamics Laboratory (GFDL) Global Circulation Model, we found that Lake Tahoe will likely cease to mix to the bottom after about 2060 for A2 scenario, with an annual mixing depth of less than 200 m as the most common value. Deep mixing, which currently occurs on average every 3-4 years, will (under the GFDL B1 scenario) occur only four times during 2061 to 2098. When the lake fails to completely mix, the bottom waters are not replenished with dissolved oxygen and eventually dissolved oxygen at these depths will be depleted to zero. When this occurs, soluble reactive phosphorus (SRP) and ammonium-nitrogen (both biostimulatory) are released from the deep sediments and contribute approximately 51 % and 14 % of the total SRP and dissolved inorganic nitrogen load, respectively. The lake model suggests that climate change will drive the lake surface level down below the natural rim after 2085 for the GFDL A2 but not the GFDL B1 scenario. The results indicate that continued climate changes could pose serious threats to the characteristics of the Lake that are most highly valued. Future water quality planning must take these results into account.
California;Nevada↗
Landscape genomics of Sphaeralcea ambigua in the Mojave Desert: a multivariate, spatially-explicit approach to guide ecological restoration
Local adaptation influences plant species’ responses to climate change and their performance in ecological restoration. Fine-scale physiological or phenological adaptations that direct demographic processes may drive intraspecific variability when baseline environmental conditions change. Landscape genomics characterize adaptive differentiation by identifying environmental drivers of adaptive genetic variability and mapping the associated landscape patterns. We applied such an approach to Sphaeralcea ambigua , an important restoration plant in the arid southwestern United States, by analyzing variation at 153 amplified fragment length polymorphism loci in the context of environmental gradients separating 47 Mojave Desert populations. We identified 37 potentially adaptive loci through a combination of genome scan approaches. We then used a generalized dissimilarity model (GDM) to relate variability in potentially adaptive loci with spatial gradients in temperature, precipitation, and topography. We identified non-linear thresholds in loci frequencies driven by summer maximum temperature and water stress, along with continuous variation corresponding to temperature seasonality. Two GDM-based approaches for mapping predicted patterns of local adaptation are compared. Additionally, we assess uncertainty in spatial interpolations through a novel spatial bootstrapping approach. Our study presents robust, accessible methods for deriving spatially-explicit models of adaptive genetic variability in non-model species that will inform climate change modelling and ecological restoration.
California, Nevada↗