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At least 1,657 records · Page 92Linked to original sources
USGS2017

Best practices for virtual participation in meetings: Experiences from synthesis centers

The earth environment is a complex system, in which collaborative scientific approaches can provide major benefits by bringing together diverse perspectives, methods, and data, to achieve robust, synthetic understanding (Fig. 1). Face-to-face scientific meetings remain extremely valuable because of the opportunity to build deep mutual trust and understanding, and develop new collaborations and sometimes even lifelong friendships (Alberts 2013, Cooke and Hilton 2015). However, it has been argued that ecologists should be particularly sensitive to the environmental footprint of travel (Fox et al. 2009); such concerns, along with the time demands for travel, particularly for multi-national working groups, provide strong motivation for exploring virtual attendance. While not replacing the richness of face-to-face interactions entirely, it is now feasible to virtually participate in meetings through services that allow video, audio, and file sharing, as well as other Web-enabled communication.

Bulletin of the Ecological Society of America↗
USGS2026

How wildlife respond to tropical cyclones: Short-term tactics and long-term impacts

From butterflies to lizards and from sharks to seabirds, wildlife exhibit tactics to survive the impacts of tropical cyclones, also known as hurricanes, cyclones, or typhoons depending on where they occur. Some species seek refuge during the storm by moving, some remain in place and ride it out, and others move longer distances, avoiding the main impacts of the storm altogether. Tropical cyclones can have direct impacts on wildlife (e.g. mortality) but can also have indirect effects by altering resources and habitat, with downstream impacts on abundance and recruitment. Using examples from across taxa and ecosystems, we explore the pathways by which tropical cyclones can influence wildlife populations and communities. We describe tactics demonstrated by wildlife that enable them to survive the immediate impacts of the storm, as well as the longer-term impacts after the storm. We give examples of tropical cyclones as a selective pressure and as a facilitator for the introduction of invasive species. We also describe how tropical cyclones may provide a net benefit to some native species. The ecological and evolutionary impacts of tropical cyclones on wildlife can be complex, as they are often intertwined with concurrent pressures from land-use change, human development, and climate change. As the frequency of intense tropical cyclones is predicted to increase globally, identifying the mechanisms by which wildlife cope with such disturbances can aid in understanding and mitigating the impacts of climate change on wildlife.

Biological Reviews↗
USGS2017

Social-ecological outcomes in recreational fisheries: The interaction of lakeshore development and stocking

Many ecosystems continue to experience rapid transformations due to processes like land use change and resource extraction. A systems approach to maintaining natural resources focuses on how interactions and feedbacks among components of complex social‐ecological systems generate social and ecological outcomes. In recreational fisheries, residential shoreline development and fish stocking are two widespread human behaviors that influence fisheries, yet emergent social‐ecological outcomes from these potentially interacting behaviors remain under explored. We applied a social‐ecological systems framework using a simulation model and empirical data to determine whether lakeshore development is likely to promote stocking through its adverse effects on coarse woody habitat and thereby also on survival of juvenile and adult fish. We demonstrate that high lakeshore development is likely to generate dependency of the ecosystem on the social system, in the form of stocking. Further, lakeshore development can interact with social‐ecological processes to create deficits for state‐level governments, which threatens the ability to fund further ecosystem subsidies. Our results highlight the value of a social‐ecological framework for maintaining ecosystem services like recreational fisheries.

Ecological Applications↗
USGS2017

Incorporating food web dynamics into ecological restoration: A modeling approach for river ecosystems

Restoration is frequently aimed at the recovery of target species, but also influences the larger food web in which these species participate. Effects of restoration on this broader network of organisms can influence target species both directly and indirectly via changes in energy flow through food webs. To help incorporate these complexities into river restoration planning we constructed a model that links river food web dynamics to in-stream physical habitat and riparian vegetation conditions. We present an application of the model to the Methow River, Washington (USA), a location of on-going restoration aimed at recovering salmon. Three restoration strategies were simulated: riparian vegetation restoration, nutrient augmentation via salmon carcass addition, and side-channel reconnection. We also added populations of nonnative aquatic snails and fish to the modeled food web to explore how changes in food web structure mediate responses to restoration. Simulations suggest that side-channel reconnection may be a better strategy than carcass addition and vegetation planting for improving conditions for salmon in this river segment. However, modeled responses were strongly sensitive to changes in the structure of the food web. The addition of nonnative snails and fish modified pathways of energy through the food web, which negated restoration improvements. This finding illustrates that forecasting responses to restoration may require accounting for the structure of food webs, and that changes in this structure—as might be expected with the spread of invasive species—could compromise restoration outcomes. Unlike habitat-based approaches to restoration assessment that focus on the direct effects of physical habitat conditions on single species of interest, our approach dynamically links the success of target organisms to the success of competitors, predators, and prey. By elucidating the direct and indirect pathways by which restoration affects target species, dynamic food web models can improve restoration planning by fostering a deeper understanding of system connectedness and dynamics.

Washington↗
USGS2017

Matching seed to site by climate similarity: techniques to prioritize plant materials development and use in restoration

Land management agencies are increasing the use of native plant materials for vegetation treatments to restore ecosystem function and maintain natural ecological integrity. This shift toward the use of natives has highlighted a need to increase the diversity of materials available. A key problem is agreeing on how many, and which, new accessions should be developed. Here we describe new methods that address this problem. Our methods use climate data to calculate a climate similarity index between two points in a defined extent. This index can be used to predict relative performance of available accessions at a target site. In addition, the index can be used in combination with standard cluster analysis algorithms to quantify and maximize climate coverage (mean climate similarity), given a modeled range extent and a specified number of accessions. We demonstrate the utility of this latter feature by applying it to the extents of 11 western North American species with proven or potential use in restoration. First, a species-specific seed transfer map can be readily generated for a species by predicting performance for accessions currently available; this map can be readily updated to accommodate new accessions. Next, the increase in climate coverage achieved by adding successive accessions can be explored, yielding information that managers can use to balance ecological and economic considerations in determining how many accessions to develop. This approach identifies sampling sites, referred to as climate centers, which contribute unique, complementary, climate coverage to accessions on hand, thus providing explicit sampling guidance for both germplasm preservation and research. We examine how these and other features of our approach add to existing methods used to guide plant materials development and use. Finally, we discuss how these new methods provide a framework that could be used to coordinate native plant materials development, evaluation, and use across agencies, regions, and research groups.

Ecological Applications↗
USGS2018

Making do with less: Must sparse data preclude informed harvest strategies for European waterbirds?

The demography of many European waterbirds is not well understood because most countries have conducted little monitoring and assessment, and coordination among countries on waterbird management has little precedent. Yet intergovernmental treaties now mandate the use of sustainable, adaptive harvest strategies, whose development is challenged by a paucity of demographic information. In this study, we explore how a combination of allometric relationships, fragmentary monitoring and research information, and expert judgment can be used to estimate the parameters of a theta-logistic population model, which in turn can be used in a Markov decision process to derive optimal harvesting strategies. We show how to account for considerable parametric uncertainty, as well as for different management objectives. We illustrate our methodology with a poorly understood population of taiga bean geese ( Anser fabalis fabalis ), which is a popular game bird in Fennoscandia. Our results for taiga bean geese suggest that they may have demographic rates similar to other, well-studied species of geese, and our model-based predictions of population size are consistent with the limited monitoring information available. Importantly, we found that by using a Markov decision process, a simple scalar population model may be sufficient to guide harvest management of this species, even if its demography is age-structured. Finally, we demonstrated how two different management objectives can lead to very different optimal harvesting strategies, and how conflicting objectives may be traded off with each other. This approach will have broad application for European waterbirds by providing preliminary estimates of key demographic parameters, by providing insights into the monitoring and research activities needed to corroborate those estimates, and by producing harvest management strategies that are optimal with respect to the managers’ objectives, options, and available demographic information.

Ecological Applications↗
USGS2019

Designing flows to enhance ecosystem functioning in heavily altered rivers

More than a century of dam construction and water development in the western United States has led to extensive ecological alteration of rivers. Growing interest in improving river function is compelling practitioners to consider ecological restoration when managing dams and water extraction. We developed an Ecological Response Model (ERM) for the Cache la Poudre River, northern Colorado, USA, to illuminate effects of current and possible future water management and climate change. We used empirical data and modeled interactions among multiple ecosystem components to capture system-wide insights not possible with the unintegrated models commonly used in environmental assessments. The ERM results showed additional flow regime modification would further alter the structure and function of Poudre River aquatic and riparian ecosystems due to multiple and interacting stressors. Model predictions illustrated that specific peak flow magnitudes in spring and early summer are critical for substrate mobilization, dynamic channel morphology, and overbank flows, with strong subsequent effects on instream and riparian biota that varied seasonally and spatially, allowing exploration of nuanced management scenarios. Instream biological indicators benefitted from higher and more stable base flows and high peak flows, but stable base flows with low peak flows were only half as effective to increase indicators. Improving base flows while reducing peak flows, as currently proposed for the Cache la Poudre River, would further reduce ecosystem function. Modeling showed that even presently depleted annual flow volumes can achieve substantially different ecological outcomes in designed flow scenarios, while still supporting social demands. Model predictions demonstrated that implementing designed flows in a natural pattern, with attention to base and peak flows, may be needed to preserve or improve ecosystem function of the Poudre River. Improved regulatory policies would include preservation of ecosystem-level, flow-related processes and adaptive management when water development projects are considered.

Colorado↗
USGS2020

Quantifying drought’s influence on moist soil seed vegetation in California’s Central Valley through time-series remote sensing

Californias Central Valley, USA is a critical component of the Pacific Flyway despite loss of more than 90% of its wetlands. Moist soil seed (MSS) wetland plants are now produced by mimicking seasonal flooding in managed wetlands to provide an essential food resource for waterfowl. Managers need MSS plant area and productivity estimates to support waterfowl conservation, yet this remains unknown at the landscape scale. Also the effects of recent drought on MSS plants have not been quantified. We generated Landsat-derived estimates of extents and productivity (seed yield or its proxy, the green chlorophyll index) of major MSS plants including watergrass (Echinochloa crusgalli) and smartweed (Polygonum spp.) (WGSW), and swamp timothy (Crypsis schoenoides) (ST) in all Central Valley managed wetlands from 20072017. We tested the effects of water year, land ownership and region on plant area and productivity with a multifactor nested analysis of variance. For the San Joaquin Valley we explored the association between water year and water supply, and we developed metrics to support management decisions. MSS plant area maps were based on a support vector machine classification of Landsat phenology metrics (2017 map overall accuracy: 89%). ST productivity maps were created with a linear regression model of seed yield (n=68, R2 = 0.53, normalized RMSE = 10.5%). The Central Valley-wide estimated area for ST in 2017 was 32,369 ha 2,524 ha (95% C.I.), and 13,012 ha 1,384 ha for WGSW. Mean ST seed yield ranged from 577 kg/ha in the Delta Basin to 365 kg/ha in the San Joaquin Basin. WGSW area and ST seed yield decreased while ST area increased in critical drought years compared to normal water years (Scheffes test, p<0.05). Greatest ST area increases occurred in the Sacramento Valley (~75%). Voluntary water deliveries increased in normal water years, and ST seed yield increased with water supply. Z-scores of ST seed yield can be used to evaluate wetland performance and aid resource allocation decisions. Updated maps will support habitat monitoring, conservation planning and water management in future years, which are likely to face greater uncertainty in water availability with climate change.

California↗
USGS2021

A Bayesian Dirichlet process community occupancy model to estimate community structure and species similarity

Community occupancy models estimate species‐specific parameters while sharing information across species by treating parameters as sampled from a common distribution. When communities consist of discrete groups, shrinkage of estimates towards the community mean can mask differences among groups. Infinite mixture models using a Dirichlet process (DP) distribution, in which the number of latent groups is estimated from the data, have been proposed as a solution. In addition to community structure, these models estimate species similarity, which allows testing hypotheses about whether traits drive species response to environmental conditions. We develop a community occupancy model (COM) using a DP distribution to model species‐level parameters. Because clustering algorithms are sensitive to dimensionality and distinctiveness of clusters, we conducted a simulation study to explore performance of the DP‐COM with different dimensions (i.e., different numbers of model parameters with species‐level DP random effects) and under varying cluster differences. Because the DP‐COM is computationally expensive, we compared its estimates to a COM with a normal random species effect. We further applied the DP‐COM model to a bird dataset from Uganda. Estimates of the number of clusters and species cluster identity improved with increasing difference among clusters and increasing dimensions of the DP; but the number of clusters was always overestimated. Estimates of number of sites occupied and species and community level covariate coefficients on occupancy probability were generally unbiased with (near‐) nominal 95% Bayesian Credible Interval coverage. Accuracy of estimates from the normal and the DP‐COM were similar. The DP‐COM clustered 166 bird species into 27 clusters regarding their affiliation with open or woodland habitat and distance to oil wells. Estimates of covariate coefficients were similar between a normal and the DP‐COM. Except sunbirds, species within a family were not more similar in their response to these covariates than the overall community. Given that estimates were consistent between the normal and the DP‐COM, and considering the computational burden for the DP models, we recommend using the DP‐COM only when the analysis focuses on community structure and species similarity, as these quantities can only be obtained under the DP‐COM.

Ecological Applications↗
USGS2021

Effects of snake fungal disease on short‐term survival, behavior, and movement in free‐ranging snakes

Pathogenic fungi are increasingly associated with epidemics in wildlife populations. Snake fungal disease (SFD, also referred to as Ophidiomycosis) is an emerging threat to snakes, taxa that are elusive and difficult to sample. Thus, assessments of the effects of SFD on populations have rarely occurred. We used a field technique to enhance detection, Passive Integrated Transponder (PIT) telemetry, and a multi‐state capture–mark–recapture model to assess SFD effects on short‐term (within‐season) survival, movement, and surface activity of two wild snake species, Regina septemvittata (Queensnake) and Nerodia sipedon (Common Watersnake). We were unable to detect an effect of disease state on short‐term survival for either species. However, we estimated Bayesian posterior probabilities of >0.99 that R. septemvittata with SFD spent more time surface‐active and were less likely to permanently emigrate from the study area. We also estimated probabilities of 0.98 and 0.87 that temporary immigration and temporary emigration rates, respectively, were lower in diseased R. septemvittata . We found evidence of elevated surface activity and lower temporary immigration rates in diseased N. sipedon , with estimated probabilities of 0.89, and found considerably less support for differences in permanent or temporary emigration rates. This study is the first to yield estimates for key demographic and behavioral parameters (survival, emigration, surface activity) of snakes in wild populations afflicted with SFD. Given the increase in surface activity of diseased snakes, future surveys of snake populations could benefit from exploring longer‐term demographic consequences of SFD and recognize that disease prevalence in surface‐active animals may exceed that of the population as a whole.

Ecological Applications↗
USGS2021

Advancing estuarine ecological forecasts: Seasonal hypoxia in Chesapeake Bay

Ecological forecasts are quantitative tools that can guide ecosystem management. The coemergence of extensive environmental monitoring and quantitative frameworks allows for widespread development and continued improvement of ecological forecasting systems. We use a relatively simple estuarine hypoxia model to demonstrate advances in addressing some of the most critical challenges and opportunities of contemporary ecological forecasting, including predictive accuracy, uncertainty characterization, and management relevance. We explore the impacts of different combinations of forecast metrics, drivers, and driver time windows on predictive performance. We also incorporate multiple sets of state-variable observations from different sources and separately quantify model prediction error and measurement uncertainty through a flexible Bayesian hierarchical framework. Results illustrate the benefits of (1) adopting forecast metrics and drivers that strike an optimal balance between predictability and relevance to management, (2) incorporating multiple data sources in the calibration data set to separate and propagate different sources of uncertainty, and (3) using the model in scenario mode to probabilistically evaluate the effects of alternative management decisions on future ecosystem state. In the Chesapeake Bay, the subject of this case study, we find that average summer or total annual hypoxia metrics are more predictable than monthly metrics and that measurement error represents an important source of uncertainty. Application of the model in scenario mode suggests that absent watershed management actions over the past decades, long-term average hypoxia would have increased by 7% compared to 1985. Conversely, the model projects that if management goals currently in place to restore the Bay are met, long-term average hypoxia would eventually decrease by 32% with respect to the mid-1980s.

Chesapeake Bay↗
USGS2022

Plant effects on and response to soil microbes in native and non-native Phragmites australis

Plant–soil feedbacks (PSFs) mediate plant community dynamics and may plausibly facilitate plant invasions. Microbially mediated PSFs are defined by plant effects on soil microbes and subsequent changes in plant performance (responses), both positive and negative. For microbial interactions to benefit invasive plants disproportionately, native and invasive plants must either (1) have different effects on and responses to soil microbial communities or (2) only respond differently to similar microbial communities. In other words, invasive plants do not need to cultivate different microbial communities than natives if they respond differently to them. However, effects and responses are not often explored separately, making it difficult to determine the underlying causes of performance differences. We performed a reciprocal-transplant PSF experiment with multiple microbial inhibition treatments to determine how native and non-native lineages of Phragmites australis affect and respond to soil bacteria, fungi, and oomycetes. Non-native Phragmites is a large, fast-growing, cosmopolitan invasive plant, whereas the North American native variety is comparatively smaller, slower growing, and typically considered a desirable wetland plant. We identified the effects of each plant lineage on soil microbes using DNA meta-barcoding and linked plant responses to microbial communities. Both Phragmites lineages displayed equally weak, insignificant PSFs. We found evidence of slight differential effects on microbial community composition, but no significant differential plant responses. Soils conditioned by each lineage differed only slightly in bacterial community composition, but not in fungal composition. Additionally, native and non-native Phragmites lineages did not significantly differ in their response to similar soil microbial communities. Neither lineage appreciably differed when plant biomass was compared between those grown in sterile and live soils. Targeted microbial inhibitor treatments revealed both lineages were negatively impacted by soil bacteria, but the negative response was stronger in non-native Phragmites . These observations were opposite of expectations from invasion theory and imply that the success of non-native Phragmites , relative to the native lineage, does not result from its interaction with soil microorganisms. More broadly, quantifying plant effects on, and responses to soil microbes separately provides detailed and nuanced insight into plant-microbial interactions and their role in invasions, which could inform management outcomes for invasive plants.

Ecological Applications↗
USGS2022

Modeling impacts of drought-induced salinity intrusion on carbon dynamics in tidal freshwater forested wetlands

Tidal freshwater forested wetlands (TFFW) provide critical ecosystem services including essential habitat for a variety of wildlife species and significant carbon sinks for atmospheric carbon dioxide. However, large uncertainties remain concerning the impacts of climate change on the magnitude and variability of carbon fluxes and storage across a range of TFFW. In this study, we developed a process-driven Tidal Freshwater Wetlands DeNitrification-DeComposition model (TFW-DNDC) that has integrated new features, such as soil salinity effects on plant productivity and soil organic matter decomposition to explore carbon dynamics in TFFW in response to drought-induced saltwater intrusion. Eight sites along the floodplains of the Waccamaw River (USA) and the Savannah River (USA) were selected to represent TFFW transition from healthy to moderately and highly salt-impacted forests, and eventually to oligohaline marshes. TFW-DNDC was calibrated and validated using field observed annual litterfall, stem growth, root growth, soil heterotrophic respiration and soil organic carbon storage. Analyses indicate that plant productivity and soil carbon sequestration in TFFW could change substantially in response to increased soil porewater salinity and reduced soil water table due to drought, but in interactive ways dependent on the river simulated. Such responses are variable due to non-linear relationships between carbon cycling processes and environmental drivers. Plant productivity, plant respiration, soil organic carbon sequestration rate and storage in the highly salt-impacted forest sites decreased significantly under drought conditions compared to normal conditions. Considering the high likelihood of healthy and moderately salt-impacted forests becoming highly salt-impacted forests under future climate change and sea-level rise, it is very likely that TFFW will lose their capacity as carbon sinks without up-slope migration.

Georgia, South Carolina↗
USGS2025

How to model a new invader? US-invaded range models outperform global or combined range models after 100 occurrences

Invasive species are an economic and ecological burden, and efforts to limit their impact are greatly improved with reliable maps based on species distribution models (SDMs). However, the potential distribution of new invaders is difficult to anticipate because they are still spreading with few observations in their invaded habitat. Therefore, an accepted practice in predicting the distribution of invasive species has been to incorporate habitat information from its entire geographic distribution (invaded and native ranges) into SDMs. Yet, this approach, due to niche shifts, niche expansions, and data deficiencies, commonly misrepresents where an invasive species is found in its new range. Here, we use time series records (invasion stages) from 13 invasive plant species in North America to explore the tension between modeling invasive species using global range and invaded range data and to determine if there is a “tipping point” at which one SDM strategy performs better than the other in predicting the ultimate distribution. At the earliest invasion stage, models developed using both invaded range and global occurrences on average performed better and had less variability across species than other model strategies at this stage. However, after as few as 100 observations of an invasive plant had been made, US-invaded range models, on average, outperformed global range models and models that combined occurrences. By building models with global and US-scale predictors, we show that higher performance of invaded range models was in part because of greater data quality at the invaded-range scale. Our work demonstrates that after relatively few observations of an invasive species in its invaded range, it is more accurate to model its potential distribution using only information from the invaded range while disregarding information from other regions. This work develops a robust and comprehensive approach to modeling novel distributions of newly observed invasive species.

North America↗
USGS2025

Optimizing control of a freshwater invader in time and space

The global spread of invasive species in aquatic ecosystems has prompted population control efforts to mitigate negative impacts on native species and ecosystem functions. Removal programs that optimally allocate removal effort across space and time offer promise for improving invader suppression or eradication, especially given the limited resources available to these programs. However, science-based guidance to inform such programs remains limited. This study leverages two intensive fish removal programs for nonnative green sunfish (Lepomis cyanellus) in intermittent streams of the Bill Williams River basin in Arizona, USA, to explore alternative management strategies involving variable allocation of removal effort in time and space and compare static versus dynamic decision rules. We used Bayesian hierarchical modeling to estimate demographic parameters using existing removal data, with evidence that both removal programs led to at least a 0.39 probability of eradication. Simulated alternative management strategies revealed that population suppression, but not eradication, could be achieved with reduced effort, and that dynamic management practices that respond to species abundance in real time can improve the efficiency of removal efforts. High removal frequency and program duration, including continued monitoring after zero fish were captured, contributed to successful population control. With management efforts struggling to keep pace with the rising spread and impacts of invasive species, this research demonstrates the utility of quantitative removal models to help improve invasive removal programs and robustly evaluate the success of population suppression and eradication.

Arizona↗
USGS2023

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

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

Ecology and Evolution↗
USGS2014

Physiological and ecological effects of increasing temperature on fish production in lakes of Arctic Alaska

Lake ecosystems in the Arctic are changing rapidly due to climate warming. Lakes are sensitive integrators of climate-induced changes and prominent features across the Arctic landscape, especially in lowland permafrost regions such as the Arctic Coastal Plain of Alaska. Despite many studies on the implications of climate warming, how fish populations will respond to lake changes is uncertain for Arctic ecosystems. Least Cisco (Coregonus sardinella) is a bellwether for Arctic lakes as an important consumer and prey resource. To explore the consequences of climate warming, we used a bioenergetics model to simulate changes in Least Cisco production under future climate scenarios for lakes on the Arctic Coastal Plain. First, we used current temperatures to fit Least Cisco consumption to observed annual growth. We then estimated growth, holding food availability, and then feeding rate constant, for future projections of temperature. Projected warmer water temperatures resulted in reduced Least Cisco production, especially for larger size classes, when food availability was held constant. While holding feeding rate constant, production of Least Cisco increased under all future scenarios with progressively more growth in warmer temperatures. Higher variability occurred with longer projections of time mirroring the expanding uncertainty in climate predictions further into the future. In addition to direct temperature effects on Least Cisco growth, we also considered changes in lake ice phenology and prey resources for Least Cisco. A shorter period of ice cover resulted in increased production, similar to warming temperatures. Altering prey quality had a larger effect on fish production in summer than winter and increased relative growth of younger rather than older age classes of Least Cisco. Overall, we predicted increased production of Least Cisco due to climate warming in lakes of Arctic Alaska. Understanding the implications of increased production of Least Cisco to the entire food web will be necessary to predict ecosystem responses in lakes of the Arctic.

Alaska↗