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At least 433 records · Page 24Linked to original sources

USGS2018

Hidden cost of disease in a free‐ranging ungulate: brucellosis reduces mid‐winter pregnancy in elk

Demonstrating disease impacts on the vital rates of free‐ranging mammalian hosts typically requires intensive, long‐term study. Evidence for chronic pathogens affecting reproduction but not survival is rare, but has the potential for wide‐ranging effects. Accurately quantifying disease‐associated reductions in fecundity is important for advancing theory, generating accurate predictive models, and achieving effective management. We investigated the impacts of brucellosis ( Brucella abortus ) on elk ( Cervus canadensis ) productivity using serological data from over 6,000 captures since 1990 in the Greater Yellowstone Ecosystem, USA. Over 1,000 of these records included known age and pregnancy status. Using Bayesian multilevel models, we estimated the age‐specific pregnancy probabilities of exposed and naïve elk. We then used repeat‐capture data to investigate the full effects of the disease on life history. Brucellosis exposure reduced pregnancy rates of elk captured in mid‐ and late‐winter. In an average year, we found 60% of exposed 2‐year‐old elk were pregnant compared to 91% of their naïve counterparts (a 31 percentage point reduction, 89% HPDI = 20%–42%), whereas exposed 3‐ to 9‐year‐olds were 7 percentage points less likely to be pregnant than naïve elk of their same age (89% HPDI = 2%–11%). We found these reduced rates of pregnancy to be independent from disease‐induced abortions, which afflict a portion of exposed elk. We estimate that the combination of reduced pregnancy by mid‐winter and the abortions following mid‐winter reduces the reproductive output of exposed female elk by 24%, which affects population dynamics to a similar extent as severe winters or droughts. Exposing hidden reproductive costs of disease is essential to avoid conflating them with the effects of climate and predation. Such reproductive costs cause complex population dynamics, and the magnitude of the effect we found should drive a strong selection gradient if there is heritable resistance.

Ecology and Evolution↗

USGS2025

Elevation mediates juvenile steelhead demographic response to stream temperature and flow

Climate change alters streams by modifying flow dynamics, temperature, and biotic communities, changing the habitat where stream dwelling fish have evolved. We used snorkel survey data spanning four decades to investigate how juvenile steelhead (anadromous Oncorhynchus mykiss ) counts and size structure were influenced by stream temperature and flow. Warmer temperatures were associated with lower abundance and larger fish at low elevations and with higher abundance and smaller fish at higher elevations. Low flows were related to increased abundance and smaller fish at low elevations but to decreased abundance at high elevations, suggesting that lower elevation streams, which tend to be larger, provided additional habitat during low flows. High flows were negatively related to abundance and positively related to average size, suggesting emigration of fish in younger age-classes. Overall, steelhead exhibited greater resilience to warm temperatures at high elevations and, conversely, greater resilience to low and high flows at lower elevations. Understanding how streamflow and temperature affect juvenile steelhead abundance and size structure provides insight into how climate change can affect juvenile steelhead production.

Idaho↗

USGS2016

Prerequisites for understanding climate-change impacts on northern prairie wetlands

The Prairie Pothole Region (PPR) contains ecosystems that are typified by an extensive matrix of grasslands and depressional wetlands, which provide numerous ecosystem services. Over the past 150 years the PPR has experienced numerous landscape modifications resulting in agricultural conversion of 75–99 % of native prairie uplands and drainage of 50–90 % of wetlands. There is concern over how and where conservation dollars should be spent within the PPR to protect and restore wetland basins to support waterbird populations that will be robust to a changing climate. However, while hydrological impacts of landscape modifications appear substantial, they are still poorly understood. Previous modeling efforts addressing impacts of climate change on PPR wetlands have yet to fully incorporate interacting or potentially overshadowing impacts of landscape modification. We outlined several information needs for building more informative models to predict climate change effects on PPR wetlands. We reviewed how landscape modification influences wetland hydrology and present a conceptual model to describe how modified wetlands might respond to climate variability. We note that current climate projections do not incorporate cyclical variability in climate between wet and dry periods even though such dynamics have shaped the hydrology and ecology of PPR wetlands. We conclude that there are at least three prerequisite steps to making meaningful predictions about effects of climate change on PPR wetlands. Those evident to us are: 1) an understanding of how physical and watershed characteristics of wetland basins of similar hydroperiods vary across temperature and moisture gradients; 2) a mechanistic understanding of how wetlands respond to climate across a gradient of anthropogenic modifications; and 3) improved climate projections for the PPR that can meaningfully represent potential changes in climate variability including intensity and duration of wet and dry periods. Once these issues are addressed, we contend that modeling efforts will better inform and quantify ecosystem services provided by wetlands to meet needs of waterbird conservation and broader societal interests such as flood control and water quality.

Wetlands↗

USGS2011

Land cover change, biogeochemical modelling of carbon stocks, and climate change in West Africa

The carbon in ecosystems exists in dynamic soil and vegetation pools which vary in amounts and cycle with the global atmosphere at varying rates. These stocks and fluxes play important roles in global carbon regulation and in the maintenance of goods and services. Changes in land cover or ecosystems result in increased or decreased fluxes to the atmosphere and play a major role in climate regulation. Carbon in soil is closely coupled to soil nitrogen and the continued mining of soil for crops or fuel without replenishment of nutrients results in decreased productivity and impacts food security. The assessment of these processes across large areas, although difficult, is aided by the integration of simulation modelling (biogeochemical and ecosystem) and remote sensing. We acquired satellite imagery for four periods from the 1960s to 2000s, trained environmental scientists from 14 countries on image analysis and interpretation, and now report systematic analyses of land cover changes in select countries of West Africa and quantify potential impacts of climate change and management at specific sites. Statistical changes and maps of land cover are documented for most countries. Senegal, for example, illustrates a 57 percent loss in dense forests between 1975 and 2000 with an even greater loss rate in the preceding 10 years. Bare soil increased 16.6 percent, often related to unproductive “badland” formation. Settlements increased 45.6 percent, and reforestation replaced bare sandy areas for sand dune stabilization. In some countries (Senegal and Ghana), the impact of these conversions and changes in land management and future projections has been incorporated into biogeochemical models to quantify carbon changes and project future carbon and crop scenarios. We present current assessments of carbon fluxes and the availability of data for these West African countries.

Conference Paper↗

USGS2025

Dynamic environments generate geographic fluctuations in population structure of an inland shorebird

Species distributions depend on fine-scale ecological processes and population growth trajectories and are influenced by climate and weather changes. However, the characterization of inter-population dynamics underlying the geographic distributions of migratory organisms remains challenging. We adopted a stable isotope approach to investigate the dynamic population geography of a terrestrial migratory bird across multiple generations. We found that the age-specific geographic source of Mountain Plovers sampled during winter shifted over four years across a latitudinal gradient. Moreover, our results show that differential effects of climate on the probability of occurrence at the wintering ground could be a driver of population turnover in a migratory species adapted to extreme environmental stochasticity (i.e., drought occurrence). We propose a framework for the identification of spatial and temporal climate and weather components and respective effects on population composition and recruitment into migratory wintering populations. Our approach is useful to reveal population compositional shifts through hydrogen stable isotope analysis while accounting for cumulative drought effects.

Ecosphere↗

USGS2016

Changes in seasonal climate outpace compensatory density-dependence in eastern brook trout

Understanding how multiple extrinsic (density-independent) factors and intrinsic (density-dependent) mechanisms influence population dynamics has become increasingly urgent in the face of rapidly changing climates. It is particularly unclear how multiple extrinsic factors with contrasting effects among seasons are related to declines in population numbers and changes in mean body size and whether there is a strong role for density-dependence. The primary goal of this study was to identify the roles of seasonal variation in climate driven environmental direct effects (mean stream flow and temperature) versus density-dependence on population size and mean body size in eastern brook trout (Salvelinus fontinalis). We use data from a 10-year capture-mark-recapture study of eastern brook trout in four streams in Western Massachusetts, USA to parameterize a discrete-time population projection model. The model integrates matrix modeling techniques used to characterize discrete population structures (age, habitat type and season) with integral projection models (IPMs) that characterize demographic rates as continuous functions of organismal traits (in this case body size). Using both stochastic and deterministic analyses we show that decreases in population size are due to changes in stream flow and temperature and that these changes are larger than what can be compensated for through density-dependent responses. We also show that the declines are due mostly to increasing mean stream temperatures decreasing the survival of the youngest age class. In contrast, increases in mean body size over the same period are the result of indirect changes in density with a lesser direct role of climate-driven environmental change.

Massachusetts↗

USGS2015

Combining state-and-transition simulations and species distribution models to anticipate the effects of climate change

State-and-transition simulation models (STSMs) are known for their ability to explore the combined effects of multiple disturbances, ecological dynamics, and management actions on vegetation. However, integrating the additional impacts of climate change into STSMs remains a challenge. We address this challenge by combining an STSM with species distribution modeling (SDM). SDMs estimate the probability of occurrence of a given species based on observed presence and absence locations as well as environmental and climatic covariates. Thus, in order to account for changes in habitat suitability due to climate change, we used SDM to generate continuous surfaces of species occurrence probabilities. These data were imported into ST-Sim, an STSM platform, where they dictated the probability of each cell transitioning between alternate potential vegetation types at each time step. The STSM was parameterized to capture additional processes of vegetation growth and disturbance that are relevant to a keystone species in the Greater Yellowstone Ecosystem—whitebark pine ( Pinus albicaulis ). We compared historical model runs against historical observations of whitebark pine and a key disturbance agent (mountain pine beetle, Dendroctonus ponderosae ), and then projected the simulation into the future. Using this combination of correlative and stochastic simulation models, we were able to reproduce historical observations and identify key data gaps. Results indicated that SDMs and STSMs are complementary tools, and combining them is an effective way to account for the anticipated impacts of climate change, biotic interactions, and disturbances, while also allowing for the exploration of management options.

AIMS Environmental Science↗

USGS2023

A coupled human and natural systems framework to characterize emerging infectious diseases: The case of fibropapillomatosis in marine turtles

Emerging infectious diseases of wildlife have markedly increased in the last few decades. Unsustainable, continuous, and rapid alterations within and between coupled human and natural systems have significantly disrupted wildlife disease dynamics. Direct and indirect anthropogenic effects, such as climate change, pollution, encroachment, urbanization, travel, and trade, can promote outbreaks of infectious diseases in wildlife. We constructed a coupled human and natural systems framework identifying three main wildlife disease risk factors behind these anthropogenic effects: (i) immune suppression, (ii) viral spillover, and (iii) disease propagation. Through complex and convoluted dynamics, each of the anthropogenic effect listed in our framework can lead, to some extent, to one or more of the identified risk factors accelerating disease outbreaks in wildlife. In this review, we present a novel framework to study anthropogenic impacts within coupled human and natural systems that facilitate emergence of infectious disease involving wildlife. We demonstrate the utility of the framework by applying it to Fibropapillomatosis disease of marine turtles. We aim to articulate the intricate and complex nature of anthropogenically-exacerbated wildlife infectious diseases as multifactorial. This paper supports the adoption of a One Health approach and invites the collaboration of multiple disciplines for the achievement of effective and long-lasting conservation and wildlife emerging diseases mitigation outcomes.

Animals↗

USGS1992

Analyzing vegetation dynamics of land systems with satellite data

Large area assessment of vegetation conditions is a major requirement for understanding the impact of weather on food, fiber, and forage production. The distribution of vegetation is largely associated with climate, terrain characteristics, and human activity. The interpretation of vegetation dynamics from satellite data can be improved by stratifying the land surface into ecoregions. The Soil Conservation Service, U.S. Department of Agriculture, has developed a system for mapping major land resource areas (MLRA) that groups land areas in the United States on the basis of climate, physiography, land use, and land cover characteristics. In 1989, the U.S. Geological Survey used National Oceanic and Atmospheric Administration weather satellite data to conduct a biweekly assessment of vegetation conditions in 17 western states. Advanced Very High Resolution Radiometer data were acquired daily, and were geographically registered, and the normalized difference vegetation index (NDVI) was computed for the Western United States during the 1989 growing season. Fifteen biweekly NDVI data sets were used to evaluate MLRA's as an appropriate stratification for monitoring and interpreting vegetation conditions in the study area. The results demonstrate the feasibility of using MLRA's to stratify areas for monitoring phenological development and vegetation condition assessment within the growing season. Assessments of the NDVI at biweekly intervals are adequate for monitoring seasonal growth patterns on MLRA's where rangelands, forests, or cultivated agriculture are the primary resource type. Descriptive statistics are indicators of the uniformity or diversity of land use and land cover within an MLRA. Growing season profiles of the NDVI are characterized by the seasonal effects of climate on various land use and land cover classes.

Geocarto International↗

USGS2016

Dynamic simulation and numerical analysis of hurricane storm surge under sea level rise with geomorphologic changes along the northern Gulf of Mexico

This work outlines a dynamic modeling framework to examine the effects of global climate change, and sea level rise (SLR) in particular, on tropical cyclone-driven storm surge inundation. The methodology, applied across the northern Gulf of Mexico, adapts a present day large-domain, high resolution, tide, wind-wave, and hurricane storm surge model to characterize the potential outlook of the coastal landscape under four SLR scenarios for the year 2100. The modifications include shoreline and barrier island morphology, marsh migration, and land use land cover change. Hydrodynamics of 10 historic hurricanes were simulated through each of the five model configurations (present day and four SLR scenarios). Under SLR, the total inundated land area increased by 87% and developed and agricultural lands by 138% and 189%, respectively. Peak surge increased by as much as 1 m above the applied SLR in some areas, and other regions were subject to a reduction in peak surge, with respect to the applied SLR, indicating a nonlinear response. Analysis of time-series water surface elevation suggests the interaction between SLR and storm surge is nonlinear in time; SLR increased the time of inundation and caused an earlier arrival of the peak surge, which cannot be addressed using a static (“bathtub”) modeling framework. This work supports the paradigm shift to using a dynamic modeling framework to examine the effects of global climate change on coastal inundation. The outcomes have broad implications and ultimately support a better holistic understanding of the coastal system and aid restoration and long-term coastal sustainability.

Earth's Future↗

USGS2021

Climate change may cause shifts in growth and instantaneous natural mortality of American Shad throughout their native range

American Shad Alosa sapidissima is an anadromous species with populations ranging along the U.S. Atlantic coast. Past American Shad stock assessments have been data limited and estimating system-specific growth parameters or instantaneous natural mortality ( M ) was not possible. This precluded system-specific stock assessment and management due to reliance on these parameters for estimating other population dynamics (such as yield per recruit). Furthermore, climate-informed biological reference points remain a largely unaddressed need in American Shad stock assessment. Population abundance estimates of American Shad and other species often rely heavily on M derived from von Bertalanffy growth function (VBGF) parameters. Therefore, we developed Bayesian hierarchical models to estimate coastwide, regional, and system-specific VBGF parameters and M using data collected from 1982 to 2017. We tested predictive performance of models that included effects of various climate variables on VBGF parameters within these models. System-specific models were better supported than regional or coast-wide models. Mean asymptotic length ( L ∞ ) decreased with increasing mean annual sea surface temperature (SST) and degree days (DD) experienced by fish during their lifetime. Although uncertain, K (Brody growth coefficient) decreased over the same range of lifetime SST and DD. Assuming no adaptation, we projected changes in VBGF parameters and M through 2099 using modeled SST from two climate projection scenarios (Representative Concentration Pathways 4.5 and 8.5). We predicted reduced growth under both scenarios, and M was projected to increase by about 0.10. It is unclear how reduced growth and increased mortality may influence population productivity or life history adaptation in the future, but our results may inform stock assessment models to assess those trade-offs.

Transactions of the American Fisheries Society↗

USGS2021

Understanding the future of big sagebrush regeneration: challenges of projecting complex ecological processes

Regeneration is an essential demographic step that affects plant population persistence, recovery after disturbances, and potential migration to track suitable climate conditions. Challenges of restoring big sagebrush ( Artemisia tridentata ) after disturbances including fire-invasive annual grass interactions exemplify the need to understand the complex regeneration processes of this long-lived, woody species that is widespread across the semiarid western U.S. Projected 21st century climate change is expected to increase drought risks and intensify restoration challenges. A detailed understanding of regeneration will be crucial for developing management frameworks for the big sagebrush region in the 21st century. Here, we used two complementary models to explore spatial and temporal relationships in the potential of big sagebrush regeneration representing (1) range-wide big sagebrush regeneration responses in natural vegetation (process-based model) and (2) big sagebrush restoration seeding outcomes following fire in the Great Basin and the Snake River Plains (regression-based model). The process-based model suggested substantial geographic variation in long-term regeneration trajectories with central and northern areas of the big sagebrush region remaining climatically suitable, whereas marginal and southern areas are becoming less suitable. The regression-based model suggested, however, that restoration seeding may become increasingly more difficult, illustrating the particularly difficult challenge of promoting sagebrush establishment after wildfire in invaded landscapes. These results suggest that sustaining big sagebrush on the landscape throughout the 21st century may climatically be feasible for many areas and that uncertainty about the long-term sustainability of big sagebrush may be driven more by dynamics of biological invasions and wildfire than by uncertainty in climate change projections. Divergent projections of the two models under 21st century climate conditions encourage further study to evaluate potential benefits of re-creating conditions of uninvaded, unburned natural big sagebrush vegetation for post-fire restoration seeding, such as seeding in multiple years and, for at least much of the northern Great Basin and Snake River Plains, the control of the fire-invasive annual grass cycle.

Ecosphere↗

USGS2007

The role of historical fire disturbance in the carbon dynamics of the pan-boreal region: A process-based analysis

[1] Wildfire is a common occurrence in ecosystems of northern high latitudes, and changes in the fire regime of this region have consequences for carbon feedbacks to the climate system. To improve our understanding of how wildfire influences carbon dynamics of this region, we used the process-based Terrestrial Ecosystem Model to simulate fire emissions and changes in carbon storage north of 45°N from the start of spatially explicit historically recorded fire records in the twentieth century through 2002, and evaluated the role of fire in the carbon dynamics of the region within the context of ecosystem responses to changes in atmospheric CO 2 concentration and climate. Our analysis indicates that fire plays an important role in interannual and decadal scale variation of source/sink relationships of northern terrestrial ecosystems and also suggests that atmospheric CO 2 may be important to consider in addition to changes in climate and fire disturbance. There are substantial uncertainties in the effects of fire on carbon storage in our simulations. These uncertainties are associated with sparse fire data for northern Eurasia, uncertainty in estimating carbon consumption, and difficulty in verifying assumptions about the representation of fires that occurred prior to the start of the historical fire record. To improve the ability to better predict how fire will influence carbon storage of this region in the future, new analyses of the retrospective role of fire in the carbon dynamics of northern high latitudes should address these uncertainties.

Journal of Geophysical Research G: Biogeosciences↗

USGS2016

Interactions among vegetation, climate, and herbivory control greenhouse gas fluxes in a subarctic coastal wetland

High-latitude ecosystems are experiencing the most rapid climate changes globally, and in many areas these changes are concurrent with shifts in patterns of herbivory. Individually, climate and herbivory are known to influence biosphere-atmosphere greenhouse gas (GHG) exchange; however, the interactive effects of climate and herbivory in driving GHG fluxes have been poorly quantified, especially in coastal systems that support large populations of migratory waterfowl. We investigated the magnitude and the climatic and physical controls of GHG exchange within the Yukon-Kuskokwim Delta in western Alaska across four distinct vegetation communities formed by herbivory and local microtopography. Net CO 2 flux was greatest in the ungrazed Carex meadow community (3.97 ± 0.58 [SE] µmol CO 2 m −2 s −1 ), but CH 4 flux was greatest in the grazed community (14.00 ± 6.56 nmol CH 4 m −2 s −1 ). The grazed community is also the only vegetation type where CH 4 was a larger contributor than CO 2 to overall GHG forcing. We found that vegetation community was an important predictor of CO 2 and CH 4 exchange, demonstrating that variation in regional gas exchange is best explained when the effect of grazing, determined by the difference between grazed and ungrazed communities, is included. Further, we identified an interaction between temperature and vegetation community, indicating that grazed regions could experience the greatest increases in CH 4 emissions with warming. These results suggest that future GHG fluxes could be influenced by both climate and by changes in herbivore population dynamics that expand or contract the vegetation community most responsive to future temperature change.

Alaska↗

USGS2019

Estimating lake–climate responses from sparse data: An application to high elevation lakes

Although many studies demonstrate lake warming, few document trends from lakes with sparse data. Diel and seasonal variability of surface temperatures limit conventional trend analyses to datasets with frequent repeated observations. Thus, remote lakes, including many high elevation lakes, are underrepresented in trend analyses. We used a Bayesian technique to analyze sparse data that explicitly incorporated diel and seasonal variability. This approach allowed us to estimate lake warming in a region of limited knowledge: high elevation lakes (> 2100 m ASL) of the Southern Rocky Mountains, U.S.A. The analysis allowed for inclusion of lakes with few repeated measurements, and observations made before 1980 when more intensive lake monitoring began. We accumulated the largest dataset of high elevation lake temperatures analyzed to date. Data from 590 high elevation lakes in the Southern Rocky Mountains showed a 0.13°C decade −1 increase in surface temperatures and a 14% increase in seasonal degree days since 1955. This result is lower than other regional and global estimates of lake warming; however, it is similar to other high elevation lake studies. Our approach can be applied to other understudied regions, increasing our overall understanding of the effects of climate change on lakes and their temporal dynamics.

Colorado↗

USGS2007

Calibrating a forest landscape model to simulate frequent fire in Mediterranean-type shrublands

In Mediterranean-type ecosystems (MTEs), fire disturbance influences the distribution of most plant communities, and altered fire regimes may be more important than climate factors in shaping future MTE vegetation dynamics. Models that simulate the high-frequency fire and post-fire response strategies characteristic of these regions will be important tools for evaluating potential landscape change scenarios. However, few existing models have been designed to simulate these properties over long time frames and broad spatial scales. We refined a landscape disturbance and succession (LANDIS) model to operate on an annual time step and to simulate altered fire regimes in a southern California Mediterranean landscape. After developing a comprehensive set of spatial and non-spatial variables and parameters, we calibrated the model to simulate very high fire frequencies and evaluated the simulations under several parameter scenarios representing hypotheses about system dynamics. The goal was to ensure that observed model behavior would simulate the specified fire regime parameters, and that the predictions were reasonable based on current understanding of community dynamics in the region. After calibration, the two dominant plant functional types responded realistically to different fire regime scenarios. Therefore, this model offers a new alternative for simulating altered fire regimes in MTE landscapes. ?? 2007 Elsevier Ltd. All rights reserved.

Environmental Modelling and Software↗

USGS2010

Geochronology and paleoclimatic implications of the last deglaciation of the Mauna Kea Ice Cap, Hawaii

We present new 3He surface exposure ages on moraines and bedrock near the summit of Mauna Kea, Hawaii, which refine the age of the Mauna Kea Ice Cap during the Local Last Glacial Maximum (LLGM) and identify a subsequent fluctuation of the ice margin. The 3He ages, when combined with those reported previously, indicate that the local ice-cap margin began to retreat from its LLGM extent at 20.5??2.5ka, in agreement with the age of deglaciation determined from LLGM moraines elsewhere in the tropics. The ice-cap margin receded to a position at least 3km upslope for ~4.5-5.0kyr before readvancing nearly to its LLGM extent. The timing of this readvance at ~15.4ka corresponds to a large reduction of the Atlantic meridional overturning circulation (AMOC) following Heinrich Event 1. Subsequent ice-margin retreat began at 14.6??1.9ka, corresponding to a rapid resumption of the AMOC and onset of the B??lling warm interval, with the ice cap melting rapidly to complete deglaciation. Additional 3He ages obtained from a flood deposit date the catastrophic outburst of a moraine-dammed lake roughly coeval with the Younger Dryas cold interval, suggesting a more active hydrological cycle on Mauna Kea at this time. A coupled mass balance and ice dynamics model is used to constrain the climate required to generate ice caps of LLGM and readvance sizes. The depression of the LLGM equilibrium line altitude requires atmospheric cooling of 4.5??1??C, whereas the mass balance modeling indicates an accompanying increase in precipitation of as much as three times that of present. We hypothesize (1) that the LLGM temperature depression was associated with global cooling, (2) that the temperature depression that contributed to the readvance occurred in response to an atmospheric teleconnection to the North Atlantic, and (3) that the precipitation enhancement associated with both events occurred in response to a southward shift in the position of the inter-tropical convergence zone (ITCZ). Such a shift in the ITCZ would have allowed midlatitude cyclones to reach Mauna Kea more frequently which would have increased precipitation at high elevations and caused additional cooling. ?? 2010 Elsevier B.V.

Earth and Planetary Science Letters↗

USGS2009

Spatial and temporal variation in distribution of larval lake whitefish in eastern Lake Ontario: signs of recovery?

The lake whitefish ( Coregonus clupeaformis ) is one of the native Lake Ontario fishes that declined severely over the past century. Recent evidence of larval lake whitefish production in a historic spawning area (Chaumont Bay) might signal a recovery of this species in New York waters. We surveyed coastal and open water areas to evaluate densities and estimate total abundance of larval lake whitefish in Chaumont Bay. Other historic spawning areas and embayments with appropriate spawning and nursery habitat were also surveyed, but only a few larvae were found outside of Chaumont Bay. Lake whitefish larvae were found in every embayment sampled within Chaumont Bay, with larval densities of nearly 600/1000 m 2 in some samples. Greatest abundances occurred in the northern sectors and near the mouth of the bay. Open water densities were generally less than half that of nearshore sites. The total bay-wide estimate for 2005 was approximately 644,000 lake whitefish larvae, but dropped to 230,000–400,000 in 2006 and 2007, respectively. Mean larval growth rates (0.36 mm/day) did not differ by year, but were consistently higher in early May than in late April. Lake whitefish production in Chaumont Bay is encouraging for this species, but the cause and persistence of the decline after 2005 can be determined only by continued monitoring. Other possible bottlenecks of survival may exist at juvenile and adult stages and could significantly affect recruitment dynamics. This species is sensitive to normal climatic fluctuations and increased variability associated with global climatic change could make winter nursery conditions unfavorable for this species.

Journal of Great Lakes Research↗