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At least 1,189 records · Page 66Linked to original sources
USGS2012

Consequences of declining snow accumulation for water balance of mid-latitude dry regions

Widespread documentation of positive winter temperature anomalies, declining snowpack and earlier snow melt in the Northern Hemisphere have raised concerns about the consequences for regional water resources as well as wildfire. A topic that has not been addressed with respect to declining snowpack is effects on ecosystem water balance. Changes in water balance dynamics will be particularly pronounced at low elevations of mid-latitude dry regions because these areas will be the first to be affected by declining snow as a result of rising temperatures. As a model system, we used simulation experiments to investigate big sagebrush ecosystems that dominate a large fraction of the semiarid western United States. Our results suggest that effects on future ecosystem water balance will increase along a climatic gradient from dry, warm and snow-poor to wet, cold and snow-rich. Beyond a threshold within this climatic gradient, predicted consequences for vegetation switched from no change to increasing transpiration. Responses were sensitive to uncertainties in climatic prediction; particularly, a shift of precipitation to the colder season could reduce impacts of a warmer and snow-poorer future, depending on the degree to which ecosystem phenology tracks precipitation changes. Our results suggest that big sagebrush and other similar semiarid ecosystems could decrease in viability or disappear in dry to medium areas and likely increase only in the snow-richest areas, i.e. higher elevations and higher latitudes. Unlike cold locations at high elevations or in the arctic, ecosystems at low elevations respond in a different and complex way to future conditions because of opposing effects of increasing water-limitation and a longer snow-free season. Outcomes of such nonlinear interactions for future ecosystems will likely include changes in plant composition and productivity, dynamics of water balance, and availability of water resources.

Global Change Biology↗
USGS2017

Climatic history of the northeastern United States during the past 3000 years

Many ecosystem processes that influence Earth system feedbacks, including vegetation growth, water and nutrient cycling, and disturbance regimes, are strongly influenced by multi-decadal to millennial-scale variations in climate that cannot be captured by instrumental climate observations. Paleoclimate information is therefore essential for understanding contemporary ecosystems and their potential trajectories under a variety of future climate conditions. With the exception of fossil pollen records, there are a limited number of northeastern US (NE US) paleoclimate archives that can provide constraints on its temperature and hydroclimate history. Moreover, the records that do exist have not been considered together. Tree-ring data indicate that the 20th century was one of the wettest of the past 500 years in the eastern US (Pederson et al., 2014), and lake-level records suggest it was one of the wettest in the Holocene (Newby et al., 2014); how such results compare with other available data remains unclear, however. Here we conduct a systematic review, assessment, and comparison of paleotemperature and paleohydrological proxies from the NE US for the last 3000 years. Regional temperature reconstructions are consistent with the long-term cooling trend (1000 BCE–1700 CE) evident in hemispheric-scale reconstructions, but hydroclimate reconstructions reveal new information, including an abrupt transition from wet to dry conditions around 550–750 CE. NE US paleo data suggest that conditions during the Medieval Climate Anomaly were warmer and drier than during the Little Ice Age, and drier than today. There is some evidence for an acceleration over the past century of a longer-term wetting trend in the NE US, and coupled with the abrupt shift from a cooling trend to a warming trend from increased greenhouse gases, may have wide-ranging implications for species distributions, ecosystem dynamics, and extreme weather events. More work is needed to gather paleoclimate data in the NE US, make inter-proxy comparisons, and improve estimates of uncertainty in the reconstructions.

Climate of the Past↗
USGS2019

Evaluating consumptive and nonconsumptive predator effects on prey density using field times series data

Determining the degree to which predation affects prey abundance in natural communities constitutes a key goal of ecological research. Predators can affect prey through both consumptive effects (CEs) and nonconsumptive effects (NCEs), although the contributions of each mechanism to the density of prey populations remain largely hypothetical in most systems. Common statistical methods applied to time series data cannot elucidate the mechanisms responsible for hypothesized predator effects on prey density (e.g., differentiate CEs from NCEs), nor provide parameters for predictive models. State space models (SSMs) applied to time series data offer a way to meet these goals. Here, we employ SSMs to assess effects of an invasive predatory zooplankter, Bythotrephes longimanus, on an important prey species, Daphnia mendotae, in Lake Michigan. We fit mechanistic models in a SSM framework to seasonal time series (1994-2012) using a recently developed, maximum likelihood-based optimization method, iterated filtering, which can overcome challenges in ecological data (e.g. nonlinearities, measurement error, and irregular sampling intervals). Our results indicate that B. longimanus strongly influences D. mendotae dynamics, with mean annual peak densities of B. longimanus observed in Lake Michigan estimated to cause a 61% reduction in D. mendotae population growth rate and a 59% reduction in peak biomass density. Further, the observed B. longimanus effect is most consistent with an NCE via reduced birth rates. The SSM approach also provided estimates for key biological parameters (e.g., demographic rates) and the contribution of dynamic stochasticity and measurement error. Our study therefore provides evidence derived directly from survey data that the invasive zooplankter B. longimanus is affecting zooplankton demographics and offer parameter estimates needed to inform predictive models that explore the effect of B. longimanus under different scenarios such as climate change.

Ecology↗
USGS1993

A primer on clothing systems for cold-weather field work

Hypothermia in cold environments can be prevented by physiological adaptation and by the proper use of cold weather clothing. The human body adjusts to cold temperature by increasing the rates of basal metabolism, specific dynamic action, and physical exercise. Heat loss is reduced by vasoconstriction. Clothing systems for cold weather reduce loss by providing insulation and protection from the elements. Satisfactory cold- weather clothing is constructed of wool fabrics or the synthetic fibers polypropylene and polyester. Outerwear suitable for cold climates is insulated with down, high-loft polyester fiberfills, or the new synthetic thin insulators. (USGS)

Open-File Report↗
USGS1993

Status and population trends of Hawaii's native waterbirds, 1977-1987

Status and population trends of Hawaiis ’ native waterbirds were examined from 1977 through 1987. Waterbird population fluctuations were analyzed in relation to rainfall and land use dynamics. Numbers of Hawaiian Duck (Koloa) ( Anus wyvilliana ) and Hawaiian Common Moorhen ( Gallinula chloropus sandvicensis ) appeared stable over time; however, surveys were limited. Increase in Black-crowned Night-Heron ( Nycticorux nycticorux ) abundance appeared linked to expansion of aquaculture, particularly on Oahu, and not to climatic events. Annual rainfall patterns help explain and predict population fluctuations and anomalous distribution patterns involving Hawaiian American Coots ( Fulica americana alai ), moorhens, and Hawaiian Black-necked Stilts ( Himantopus mexicanus knudseni ). Coot, stilt, and moorhen populations fluctuated with climatic events, and intraisland dispersal to ephemeral wetlands occurred. Stilts exhibited regular inter-island migratory behavior, but coots dispersed in relation to major rainfall events. Seasonal fluctuation recorded for coots by past observers is the result of survey techniques not accounting for seasonal dispersal patterns.

Hawai'i↗
USGS2009

Coastal sensitivity to sea level rise— A focus on the Mid-Atlantic Region

This Synthesis and Assessment Product (SAP), developed as part of the U.S. Climate Change Science Program, examines potential effects of sea-level rise from climate change during the twenty-first century, with a focus on the mid-Atlantic coast of the United States. Using scientific literature and policy-related documents, the SAP describes the physical environments; potential changes to coastal environments, wetlands, and vulnerable species; societal impacts and implications of sea-level rise; decisions that may be sensitive to sea-level rise; opportunities for adaptation; and institutional barriers to adaptation. The SAP also outlines the policy context in the mid-Atlantic region and describes the implications of sea-level rise impacts for other regions of the United States. Finally, this SAP discusses ways natural and social science research can improve understanding and prediction of potential impacts to aid planning and decision making. Projections of sea-level rise for the twenty-first century vary widely, ranging from several centimeters to more than a meter. Rising sea level can inundate low areas and increase flooding, coastal erosion, wetland loss, and saltwater intrusion into estuaries and freshwater aquifers. Existing elevation data for the mid-Atlantic United States do not provide the degree of confidence needed for local decision making. Systematic nationwide collection of high-resolution elevation data would improve the ability to conduct detailed assessments in support of planning. The coastal zone is dynamic and the response of coastal areas to sea-level rise is more complex than simple inundation. Much of the United States consists of coastal environments and landforms such as barrier islands and wetlands that will respond to sea-level rise by changing shape, size, or position. The combined effects of sea-level rise and other climate change factors such as storms may cause rapid and irreversible coastal change. All these changes will affect coastal habitats and species. Increasing population and development in coastal areas also affects the ability of natural ecosystems to adjust to sea-level rise. Coastal communities and property owners have responded to coastal hazards by erecting shore protection structures, elevating land and buildings, or relocating inland. Accelerated sea-level rise would increase the costs and environmental impacts of these responses. Shoreline armoring can eliminate the land along the shore to which the public has access; beach nourishment projects often increase access to the shore. Preparing for sea-level rise can be justified in many cases, because the cost of preparing now is small compared to the cost of reacting later. Examples include wetland protection, flood insurance, longlived infrastructure, and coastal land-use planning. Nevertheless, preparing for sea-level rise has been the exception rather than the rule. Most coastal institutions were based on the implicit assumption that sea level and shorelines are stable. Efforts to plan for sea-level rise can be thwarted by several institutional biases, including government policies that encourage coastal development, flood insurance maps that do not consider sea-level rise, federal policies that prefer shoreline armoring over soft shore protection, and lack of plans delineating which areas would be protected or not as sea level rises. The prospect of accelerated sea-level rise and increased vulnerability in coastal regions underscores the immediate need for improving our scientific understanding of and ability to predict the effects of sea-level rise on natural systems and society. These actions, combined with development of decision support tools for taking adaptive actions and an effective public education program, can lessen the economic and environmental impacts of sea-level rise.

Report↗
USGS2010

Resilience of Alaska’s boreal forest to climatic change

This paper assesses the resilience of Alaska’s boreal forest system to rapid climatic change. Recent warming is associated with reduced growth of dominant tree species, plant disease and insect outbreaks, warming and thawing of permafrost, drying of lakes, increased wildfire extent, increased postfire recruitment of deciduous trees, and reduced safety of hunters traveling on river ice. These changes have modified key structural features, feedbacks, and interactions in the boreal forest, including reduced effects of upland permafrost on regional hydrology, expansion of boreal forest into tundra, and amplification of climate warming because of reduced albedo (shorter winter season) and carbon release from wildfires. Other temperature-sensitive processes for which no trends have been detected include composition of plant and microbial communities, long-term landscape-scale change in carbon stocks, stream discharge, mammalian population dynamics, and river access and subsistence opportunities for rural indigenous communities. Projections of continued warming suggest that Alaska’s boreal forest will undergo significant functional and structural changes within the next few decades that are unprecedented in the last 6000 years. The impact of these social–ecological changes will depend in part on the extent of landscape reorganization between uplands and lowlands and on policies regulating subsistence opportunities for rural communities.

Alaska↗
USGS2011

A promising tool for subsurface permafrost mapping-An application of airborne geophysics from the Yukon River Basin, Alaska

Permafrost is a predominant physical feature of the Earth's Arctic and Subarctic clines and a major consideration encompassing ecosystem structure to infrastructure engineering and placement. Perennially frozen ground is estimated to cover about 85 percent of the state of Alaska where northern reaches are underlain with continuous permafrost and parts of interior Alaska are underlain by areas of discontinuous and (or) sporadic permafrost (fig. 1). The region of Interior Alaska, where permafrost is scattered among unfrozen ground, is a complex mosaic of terrains and habitats. Such diversity creates arrays of lakes and surface-water and groundwater patterns that continental populations of migratory waterfowl and internationally significant fisheries have adapted to over time. A road or pipeline might pass over frozen and unfrozen ground, affecting the types of materials and engineering approaches needed to sustain the infrastructure. Effective mapping of discontinuous permafrost at scales meaningful ecologically and (or) from an engineering perspective has been a long-standing challenge. Using techniques such as borehole logging for site-specific assessments or botanical techniques that can suggest underlying permafrost distributions can be labor intensive and difficult to accomplish at the scale and remoteness of much of Alaska. The climate is changing in the Arctic and Subarctic regions. The warming observed throughout much of Alaska could create widespread changes in permafrost. How the warming of the permafrost affects near-surface processes, ecosystems, and community infrastructure and ecosystems is not clear. A better understanding of the dynamic distribution and physical properties of permafrost, from continuous to discontinuous, will provide knowledge of how the permafrost environment may change in the future and help inform engineering and natural resource response strategies. Here we discuss an application of an airborne remote sensing methodology for mapping and shade imaging permafrost characteristics at various scales. This work provides the first look into three-dimensional distribution of permafrost in the areas around Fort Yukon and is a demonstration of the application of airborne electromagnetic (AEM) to permafrost mapping. Such an approach is attractive, particularly in Arctic and Subarctic studies, where ground access is difficult and ecosystems are fragile. In June 2010, the U.S. Geological Survey (USGS) conducted an AEM survey near Fort Yukon, Alaska. The primary focus of this survey was to map the distribution of permafrost in selected areas in order to supply information for the development of groundwater models of the Yukon River Basin. However, the methodologies have more far-reaching ecological and engineering applications. Approximately 1,800 line kilometers were acquired in a combination of typical block style surveying in the immediate area of Fort Yukon and in long reconnaissance lines over a broader area. The widely spaced lines were flown to cross the modern Yukon River in "X" like patterns with intersections at features that have been previously studied (fig. 2). AEM is used to gather data on the electrical resistivity of materials in the subsurface below the flight path of the helicopter, which are then analyzed to interpret the subsurface lithology and the location and extent of permafrost. For this survey, the electrical resistivity was imaged to depths on the order of 50-100 meters. Images from the survey can be qualitatively compared with known permafrost features and suggest new permafrost features. Electrical properties of earth materials are affected by lithology as well as temperature and the presence of ice; frozen materials become substantially more resistive. This allows for the identification of permafrost from the resistivity image (Abraham and others, 2011). In the area of Fort Yukon, the AEM survey shows elevated resistivities extending to depth, likely indicative of thick permafrost. This depth corresponds well to observations from a borehole drilled in the area in the late 1990s, which detected permafrost to a depth of about 100 meters (Clark and others, 2009). In contrast to the area of Fort Yukon, the Yukon River and its floodplain are not associated with deep resistive sediments, suggesting a lack of deep permafrost, at least within the depth range of the AEM mapping (fig. 3).

Yukon River Basin↗
USGS2017

Historical analysis of riparian vegetation change in response to shifting management objectives on the Middle Rio Grande

Riparian ecosystems are valuable to the ecological and human communities that depend on them. Over the past century, they have been subject to shifting management practices to maximize human use and ecosystem services, creating a complex relationship between water policy, management, and the natural ecosystem. This has necessitated research on the spatial and temporal dynamics of riparian vegetation change. The San Acacia Reach of the Middle Rio Grande has experienced multiple management and river flow fluctuations, resulting in threats to its riparian and aquatic ecosystems. This research uses remote sensing data, GIS, a review of management decisions, and an assessment of climate to both quantify how riparian vegetation has been altered over time and provide interpretations of the relationships between riparian change and shifting climate and management objectives. This research focused on four management phases from 1935 to 2014, each highlighting different management practices and climate-driven river patterns, providing unique opportunities to observe a direct relationship between river management, climate, and riparian response. Overall, we believe that management practices coupled with reduced surface river-flows with limited overbank flooding influenced the compositional and spatial patterns of vegetation, including possibly increasing non-native vegetation coverage. However, recent restoration efforts have begun to reduce non-native vegetation coverage.

New Mexico↗
USGS2016

The statistical power to detect cross-scale interactions at macroscales

Macroscale studies of ecological phenomena are increasingly common because stressors such as climate and land-use change operate at large spatial and temporal scales. Cross-scale interactions (CSIs), where ecological processes operating at one spatial or temporal scale interact with processes operating at another scale, have been documented in a variety of ecosystems and contribute to complex system dynamics. However, studies investigating CSIs are often dependent on compiling multiple data sets from different sources to create multithematic, multiscaled data sets, which results in structurally complex, and sometimes incomplete data sets. The statistical power to detect CSIs needs to be evaluated because of their importance and the challenge of quantifying CSIs using data sets with complex structures and missing observations. We studied this problem using a spatially hierarchical model that measures CSIs between regional agriculture and its effects on the relationship between lake nutrients and lake productivity. We used an existing large multithematic, multiscaled database, LAke multiscaled GeOSpatial, and temporal database (LAGOS), to parameterize the power analysis simulations. We found that the power to detect CSIs was more strongly related to the number of regions in the study rather than the number of lakes nested within each region. CSI power analyses will not only help ecologists design large-scale studies aimed at detecting CSIs, but will also focus attention on CSI effect sizes and the degree to which they are ecologically relevant and detectable with large data sets.

Ecosphere↗
USGS2022

Environmental drivers of demography and potential factors limiting the recovery of an endangered marine top predator

Understanding what drives changes in wildlife demography is fundamental to the conservation and management of depleted or declining populations, though making inference about the intrinsic and extrinsic factors that influence survival and reproduction remains challenging. Here we use mark–resight data from 2000 to 2018 to examine the effects of environmental variability on age-specific survival and natality for the endangered western distinct population segment (wDPS) of Steller sea lions ( Eumetopias jubatus ) in Alaska, USA. Though this population has been studied extensively over the last four decades, the causes of divergent abundance trends that have been observed across the wDPS range remain unknown. We developed a Bayesian multievent mark–resight model that accounts for female reproductive state uncertainty. Annual survival probabilities for male pups (0.44; 0.36–0.53), female yearlings (0.63; 0.49–0.73), and male yearlings (0.62; 0.51–0.71) born in the western portion of the wDPS range, estimated here for the first time, were lower than those in the eastern portion of the wDPS range, estimated as: male pups (0.69; 0.65–0.74), female yearlings (0.76; 0.71–0.81), and male yearlings (0.71; 0.65–0.78). There was a higher proportion of young female breeders in the western portion of the range, but overall natality was lower (0.69; 0.47–0.96) than in the eastern portion of the range (0.80; 0.74–0.84). Additionally, pup mass had a positive effect on pup survival in the eastern portion of the range and a negative effect in the western portion of the range, potentially due to earlier weaning of heavier pups. Local- and basin-scale oceanographic features such as the Aleutian Low, the Arctic Oscillation Index, the North Pacific Gyre Oscillation, chlorophyll concentration, upwelling, and wind in certain seasons were correlated with vital rates. However, drawing strong inferences from these correlations is challenging given that relationships between ocean conditions and an adaptive top predator in a dynamic ecosystem are exceedingly complex. This study provides the first demographic rate estimates for the western portion of the range where abundance estimates continue to decline. These results will advance efforts to identify factors driving regionally divergent abundance trends, with implications for population-level responses to future climate variability.

Alaska↗
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↗
USGS2024

Simulation of groundwater-flow dynamics in the U.S. Northern High Plains driven by multi-model estimates of surficial aquifer recharge

There is growing interest in incorporating higher-resolution groundwater modeling within the framework of large-scale land surface models (LSMs), including processes such as three-dimensional flow, variable soil saturation, and surface water/groundwater interactions. Conversely, complex groundwater models (e.g., the U.S. Geological Survey Groundwater-Flow Model, MODFLOW) often use simpler representations of land surface dynamics (e.g., surface vegetation, evapotranspiration, recharge) and may benefit from higher process fidelity and temporal resolutions in these inputs. This study investigates the potential of improving groundwater representation in LSMs and land surface dynamics in MODFLOW through forcing MODFLOW with recharge from LSMs. Groundwater simulations build on an existing and well-calibrated MODFLOW model of the U.S. Northern High Plains aquifer, a hydrologically complex basin under the dual impacts of conversion of native vegetation to intense irrigated agricultural fields and climate change. Simulated groundwater recharge from four different land models are used to drive MODFLOW groundwater simulations. Results show relatively large discrepancies between recharge estimates among simulations. Forcing MODFLOW using recharge simulated by some of the LSMs in place of a simple water balance model marginally improves MODFLOW groundwater simulation. Further, our results support the efficacy of coupling LSMs to a sophisticated groundwater model such as MODFLOW. The coupling results in notable improvements in matching the historical groundwater levels through reduction of the skewness coefficient in percent bias histogram (from 1.50 and 1.41 in original LSMs to 0.44 and 0.27, respectively, when MODFLOW is forced by groundwater recharge from LSMs) and reduction of bias. This modeling effort seeks to identify the best compromise between comprehensive land surface processes from global LSMs and advanced representation of groundwater from regional models.

Journal of Hydrology↗
USGS2020

How repeatable is CTmax within individual brook trout over short- and long-time intervals?

As stream temperatures increase due to factors such as heated runoff from impervious surfaces, deforestation, and climate change, fish species adapted to cold water streams are forced to move to more suitable habitat, acclimate or adapt to increased thermal regimes, or die. To estimate the potential for adaptation, a (within individual) repeatable metric of thermal tolerance is imperative. Critical thermal maximum (CTmax) is a dynamic test that is widely used to measure thermal tolerance across many taxa and has been used in fishes for decades, but its repeatability in most species is unknown. CTmax tests increase water temperature steadily over time until loss of equilibrium (LOE) is achieved. To determine if CTmax is a consistent metric within individual fish, we measured CTmax on the same lab-held individually-marked adult brook trout Salvelinus fontinalis at three different times (August & September 2016, September 2017). We found that CTmax is a repeatable trait (Repeatability ± S.E.: 0.48 ± 0.14). CTmax of individuals males was consistent over time, but the CTmax of females increased slightly over time. This result indicates that CTmax is a robust, repeatable estimate of thermal tolerance in a cold-water adapted fish.

Journal of Thermal Biology↗
USGS2023

A big data–model integration approach for predicting epizootics and population recovery in a keystone species

Infectious diseases pose a significant threat to global health and biodiversity. Yet, predicting the spatiotemporal dynamics of wildlife epizootics remains challenging. Disease outbreaks result from complex nonlinear interactions among a large collection of variables that rarely adhere to the assumptions of parametric regression modeling. We adopted a nonparametric machine learning approach to model wildlife epizootics and population recovery, using the disease system of colonial black-tailed prairie dogs (BTPD, Cynomys ludovicianus ) and sylvatic plague as an example. We synthesized colony data between 2001 and 2020 from eight USDA Forest Service National Grasslands across the range of BTPDs in central North America. We then modeled extinctions due to plague and colony recovery of BTPDs in relation to complex interactions among climate, topoedaphic variables, colony characteristics, and disease history. Extinctions due to plague occurred more frequently when BTPD colonies were spatially clustered, in closer proximity to colonies decimated by plague during the previous year, following cooler than average temperatures the previous summer, and when wetter winter/springs were preceded by drier summers/falls. Rigorous cross-validations and spatial predictions indicated that our final models predicted plague outbreaks and colony recovery in BTPD with high accuracy (e.g., AUC generally >0.80). Thus, these spatially explicit models can reliably predict the spatial and temporal dynamics of wildlife epizootics and subsequent population recovery in a highly complex host–pathogen system. Our models can be used to support strategic management planning (e.g., plague mitigation) to optimize benefits of this keystone species to associated wildlife communities and ecosystem functioning. This optimization can reduce conflicts among different landowners and resource managers, as well as economic losses to the ranching industry. More broadly, our big data–model integration approach provides a general framework for spatially explicit forecasting of disease-induced population fluctuations for use in natural resource management decision-making.

Arizona, Colorado, Kansas, Montana, Nebraska, New ↗
USGS2020

Freezing in a warming climate: Marked declines of a subnivean hibernator after a snow drought

Recent snow droughts associated with unusually warm winters are predicted to increase in frequency and affect species dependent upon snowpack for winter survival. Changes in populations of some cold‐adapted species have been attributed to heat stress or indirect effects on habitat from unusually warm summers, but little is known about the importance of winter weather to population dynamics and how responses to snow drought vary among sympatric species. We evaluated changes in abundance of hoary marmots ( Marmota caligata ) over a period that included a year of record‐low snowpack to identify mechanisms associated with weather and snowpack. To consider interspecies comparisons, our analysis used the same a priori model set as a concurrent study that evaluated responses of American pikas ( Ochotona princeps ) to weather and snowpack in the same study area of North Cascades National Park, Washington, USA. We hypothesized that marmot abundance reflected mechanisms related to heat stress, cold stress, cold exposure without an insulating snowpack, snowpack duration, atmospheric moisture, growing‐season precipitation, or select combinations of these mechanisms. Changes in marmot abundances included a 74% decline from 2007 to 2016 and were best explained by an interaction of chronic dryness with exposure to acute cold without snowpack in winter. Physiological stress during hibernation from exposure to cold, dry air appeared to be the most likely mechanism of change in marmot abundance. Alternative mechanisms associated with changes to winter weather, including early emergence from hibernation or altered vegetation dynamics, had less support. A post hoc assessment of vegetative phenology and productivity did not support vegetation dynamics as a primary driver of marmot abundance across years. Although marmot and pika abundances were explained by strikingly similar models over periods of many years, details of the mechanisms involved likely differ between species because pika abundances increased in areas where marmots declined. Such differences may lead to diverging geographic distributions of these species as global change continues.

Washington↗
USGS2021

Small atoll fresh groundwater lenses respond to a combination of natural climatic cycles and human modified geology

Freshwater lenses underlying small ocean islands exhibit spatial variability and temporal fluctuations in volume, influencing ecologic management. For example, The Palmyra Atoll National Wildlife Refuge harbors one of the few surviving native stands of Pisonia grandis in the central Pacific Ocean, yet these trees face pressure from groundwater salinization, with little basic groundwater data to guide decision making. Adding to natural complexity, the geology of Palmyra was heavily altered by dredge and fill activities. Our study based at this atoll combines geophysical and hydrological field measurements from 2008 to 2019 with groundwater modeling to study the drivers of observed freshwater lens dynamics. Electromagnetic induction (EMI) field data were collected on the main atoll islands over repeat transects in 2008 following ‘strong’ La Niña conditions (wet) and in 2016 during ‘very strong’ El Niño conditions (dry). Shallow monitoring wells were installed adjacent to the geophysical transects in 2013 and screened within the fresh/saline groundwater transition zone. Temporal EMI and monitoring well data showed a strong contraction of the freshwater lens in response to El Niño conditions, and indicated a thicker lens toward the ocean side, an opposite spatial pattern to that observed for many other Pacific islands. On an outer islet where a stand of mature Pisonia trees exist, EMI surveys revealed only a thin (<3 m from land surface) layer of brackish groundwater during El Niño. Numerical groundwater simulations were performed for a range of permeability distributions and climate conditions at Palmyra. Results revealed that the observed atypical lens asymmetry is likely due to more efficient submarine groundwater discharge on the lagoon side as a result of lagoon dredging and filling with high-permeability material. Simulations also predict large decreases (40%) in freshwater lens volume during dry cycles and highlight threats to the Pisonia trees, yielding insight for atoll ecosystem management worldwide.

Science of the Total Environment↗
USGS2022

Disentangling direct and indirect effects of extreme events on coastal wetland communities

One of the primary ways in which climate change will impact coastal freshwater wetlands is through changes in the frequency, intensity, timing and distribution of extreme weather events. Disentangling the direct and indirect mechanisms of population- and community-level responses to extreme events is vital to predicting how species composition of coastal wetlands will change under future conditions. We extended static structural equation modelling approaches to incorporate system dynamics in a multi-year multispecies occupancy model to quantify the effects of extreme weather events on a coastal freshwater wetland system. We used data from an 8-year study (2009–2016) on St. Marks National Wildlife Refuge in Florida, USA, to quantify species-specific and community-level changes in amphibian and fish occupancy associated with two flooding events in 2012 and 2013. We examine how physical changes to the landscape, including potential changes in salinity and increased wetland connectivity, may have contributed to or exacerbated the effects of these extreme weather events on the biota of isolated coastal wetlands. We provide evidence that the primary effects of flooding on the amphibian community were through indirect mechanisms via changes in the composition of the sympatric fish community that may have had lethal (i.e. through direct predation) or non-lethal (i.e. through direct or indirect competitive interactions) effects. In addition, we have shown that amphibian species differed in their sensitivity to direct flooding effects and indirect changes in the fish community and wetland-specific conductance, which led to variable responses across the community. These effects led to the overall decline in amphibian species richness from 2009 to 2016, suggesting that wetland-breeding amphibian communities on St. Marks National Wildlife Refuge may not be resilient to predicted changes in coastal disturbance regimes because of climate change. Understanding both direct and indirect effects, as well as species interactions, is important for predicting the effects of a changing climate on individual species, communities and ecosystems.

Journal of Animal Ecology↗