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At least 937 records · Page 52Linked to original sources
USGS2026

Short-term estuarine phytoplankton dynamics in response to hurricanes along the Gulf Coast of America: A Variational Autoencoder (VAE) approach with satellite and bio-optical observations

Hurricanes drive diverse estuarine phytoplankton responses and can trigger cascading ecological and physicochemical impacts. Capturing these short-term dynamics requires high spatiotemporal resolution. Here, we applied a globally-applicable coastal ocean color algorithm, Variational Autoencoder (VAE), to Sentinel-2 MSI imagery for chlorophyll- a (Chl- a ) estimation and validated its strong performance across the northern Gulf coast of America (GoA) estuaries, including Galveston Bay (TX), Barataria-Terrebonne Estuary (LA), Apalachicola Estuary (FL) and Tampa Bay (FL). The test set showed strong performance (MAE: 1.44 mg m −3 ; RMSE: 17.7 mg m −3 ; slope: 0.86; median symmetric accuracy: 30.33%). The validated VAE was then applied to 76 Sentinel-2 MSI images to assess phytoplankton biomass responses to hurricanes Harvey (2017), Michael (2018), Ida (2021), Francine (2024), Helene (2024), and Milton (2024) in the GoA estuaries. Results showed that hurricane disturbances on Chl- a typically lasted 3–5 weeks. Estuarine waters west (left) of hurricane tracks showed a rapid decline in Chl- a (∼5 mg m −3 ) due to elevated turbidity from heavy rainfall, and wind-driven flushing in the estuary, followed by a rebound over about two weeks, with Chl- a increasing approximately 10–15 mg m −3 above pre-storm levels. In contrast, right-side waters showed a slower response, likely from oligotrophic seawater intrusion driven by the hurricane's counterclockwise rotation. Post-storm observations showed increased freshwater phytoplankton like chlorophytes and cyanobacteria dominating estuaries, while shelf-waters exhibited elevated dinoflagellates (e.g., Karenia brevis bloom after Hurricane Milton). These results highlight the spatial heterogeneity of hurricane impacts on estuarine phytoplankton dynamics, which may trigger cascading effects on biogeochemical cycling and food webs, potentially prolonging ecosystem recovery.

Alabama, Florida, Louisiana, Mississippi, Texas↗
USGS2017

Restoring monarch butterfly habitat in the Midwestern US: 'All hands on deck'

The eastern migratory population of monarch butterflies ( Danaus plexippus plexippus ) has declined by >80% within the last two decades. One possible cause of this decline is the loss of ≥1.3 billion stems of milkweed ( Asclepias spp.), which monarchs require for reproduction. In an effort to restore monarchs to a population goal established by the US Fish and Wildlife Service and adopted by Mexico, Canada, and the US, we developed scenarios for amending the Midwestern US landscape with milkweed. Scenarios for milkweed restoration were developed for protected area grasslands, Conservation Reserve Program land, powerline, rail and roadside rights of way, urban/suburban lands, and land in agricultural production. Agricultural land was further divided into productive and marginal cropland. We elicited expert opinion as to the biological potential (in stems per acre) for lands in these individual sectors to support milkweed restoration and the likely adoption (probability) of management practices necessary for affecting restoration. Sixteen of 218 scenarios we developed for restoring milkweed to the Midwestern US were at levels (>1.3 billion new stems) necessary to reach the monarch population goal. One of these scenarios would convert all marginal agriculture to conserved status. The other 15 scenarios converted half of marginal agriculture (730 million stems), with remaining stems contributed by other societal sectors. Scenarios without substantive agricultural participation were insufficient for attaining the population goal. Agricultural lands are essential to reaching restoration targets because they occupy 77% of all potential monarch habitat. Barring fundamental changes to policy, innovative application of economic tools such as habitat exchanges may provide sufficient resources to tip the balance of the agro-ecological landscape toward a setting conducive to both robust agricultural production and reduced imperilment of the migratory monarch butterfly.

Conservation Letters↗
USGS2014

Combined multibeam and bathymetry data from Rhode Island Sound and Block Island Sound: a regional perspective

Detailed bathymetric maps of the sea floor in Rhode Island and Block Island Sounds are of great interest to the New York, Rhode Island, and Massachusetts research and management communities because of this area's ecological, recreational, and commercial importance. Geologically interpreted digital terrain models from individual surveys provide important benthic environmental information, yet many applications of this information require a geographically broader perspective. For example, individual surveys are of limited use for the planning and construction of cross-sound infrastructure, such as cables and pipelines, or for the testing of regional circulation models. To address this need, we integrated 14 contiguous multibeam bathymetric datasets that were produced by the National Oceanic and Atmospheric Administration during charting operations into one digital terrain model that covers much of Block Island Sound and extends eastward across Rhode Island Sound. The new dataset, which covers over 1244 square kilometers, is adjusted to mean lower low water, gridded to 4-meter resolution, and provided in Universal Transverse Mercator Zone 19, North American Datum of 1983 and geographic World Geodetic Survey of 1984 projections. This resolution is adequate for sea-floor feature and process interpretation but is small enough to be queried and manipulated with standard Geographic Information System programs and to allow for future growth. Natural features visible in the data include boulder lag deposits of winnowed Pleistocene strata, sand-wave fields, and scour depressions that reflect the strength of oscillating tidal currents and scour by storm-induced waves. Bedform asymmetry allows interpretations of net sediment transport. Anthropogenic features visible in the data include shipwrecks and dredged channels. Together the merged data reveal a larger, more continuous perspective of bathymetric topography than previously available, providing a fundamental framework for research and resource management activities offshore of Rhode Island.

Rhode Island↗
USGS2016

Cyanobacterial harmful algal blooms and U.S. Geological Survey science capabilities

Cyanobacterial harmful algal blooms (CyanoHABs) are increasingly a global concern because CyanoHABs pose a threat to human and aquatic ecosystem health and cause economic damages. Despite advances in scientific understanding of cyanobacteria and associated compounds, many unanswered questions remain about occurrence, environmental triggers for toxicity, and the ability to predict the timing, duration, and toxicity of CyanoHABs. U.S. Geological Survey (USGS) scientists are leading a diverse range of studies to address CyanoHAB issues in water bodies throughout the United States, using a combination of traditional methods and emerging technologies, and in collaboration with numerous partners. By providing practical applications of cutting edge CyanoHAB research, USGS studies have advanced scientific understanding, enabling the development of approaches to help protect ecological and human health.

Open-File Report↗
USGS2016

Federal collaboration in science for invasive mammal management in U.S. National Parks and Wildlife Refuges of the Pacific Islands

Some of the most isolated islands in the Pacific Ocean are home to US National Parks and Wildlife Refuges. These islands are known for flora and fauna that occur nowhere else, but also for invasive species and other factors which have resulted in the disproportionate extinction of native species. The control of invasive mammals is the single most expensive natural resource management activity essential for restoring ecological integrity to parks in the Hawaiian Islands, American Samoa, and the islands of Guam and Saipan. Science-based applications supporting management efforts have been shaped by longstanding collaborative federal research programs over the past four decades. Consequently, feral goats (Capra hircus) have been removed from >690 km2 in National Parks, and feral pigs (Sus scrofa) have been removed from >367 km2 of federal lands of Hawai‘i, bringing about the gradual recovery of forest ecosystems. The exclusion of other non-native ungulates and invasive mammals is now being undertaken with more sophisticated control techniques and fences. New fence designs are now capable of excluding feral cats (Felis catus) from large areas to protect endangered native waterfowl and nesting seabirds. Rodenticides which have been tested and registered for hand and aerial broadcast in Hawai‘i have been used to eradicate rats from small offshore islands to protect nesting seabirds and are now being applied to montane environments of larger islands to protect forest birds. Forward-looking infrared radar (FLIR) is also being applied to locate wild ungulates which were more recently introduced to some islands. All invasive mammals have been eradicated from some remote small islands, and it may soon be possible to manage areas on larger islands to be free of invasive mammals at least during seasonally important periods for native species.

Conference Paper↗
USGS2012

Morphometric-based sexual determination of Bananaquits (Coereba flaveola)

The Bananaquit (Coereba flaveola) is a common passerine throughout the tropics and has been a convenient species for ecological studies. This species has sexually monomorphic plumage and cannot be reliably sexed unless in breeding condition. This is problematic for demographic and comparative studies, which are contingent upon accurately aging and sexing individuals. Although male Bananaquits are larger than females, there is overlap in both wing chord and mass. We used morphometric data collected over eight years to develop a predictive model based on logistic regression to assign adult Bananaquits to sex. Our model classified 96% of validation individuals to the correct sex. We suggest that this approach may enhance ecological studies of the species by facilitating correct sex determination independent of breeding status. We believe our modeling approach is applicable elsewhere but, because there may be geographical variation across the species distribution, models will need to be customized to local populations.

Guana Island↗
USGS2011

Adaptive resource management and the value of information

The value of information is a general and broadly applicable concept that has been used for several decades to aid in making decisions in the face of uncertainty. Yet there are relatively few examples of its use in ecology and natural resources management, and almost none that are framed in terms of the future impacts of management decisions. In this paper we discuss the value of information in a context of adaptive management, in which actions are taken sequentially over a timeframe and both future resource conditions and residual uncertainties about resource responses are taken into account. Our objective is to derive the value of reducing or eliminating uncertainty in adaptive decision making. We describe several measures of the value of information, with each based on management objectives that are appropriate for adaptive management. We highlight some mathematical properties of these measures, discuss their geometries, and illustrate them with an example in natural resources management. Accounting for the value of information can help to inform decisions about whether and how much to monitor resource conditions through time.

Ecological Modelling↗
USGS2022

Spatial dynamic N-mixture models with interspecific interactions

Interspecific interactions and movement are key factors that drive the coexistence of metapopulations in heterogenous landscapes. Yet, it is challenging to understand these factors because separating movement from local population processes relied on capture-based data that are difficult to collect. Recent development of spatial dynamic N-mixture models (SDNMs) made it possible to draw inference on local population growth and movement using count data of unmarked populations. However, no SDNMs have been developed to account for interspecific interactions and double counting observation errors. In this study we further developed SDNMs to account for interspecific interactions and both false negative and double counting observation errors. We conducted simulation studies to evaluate the inferential performance of these models under different ecological systems (competition, predator-prey), observation processes (binomial, Poisson), and sampling situations including the number of surveyed sites, detection, and the adoption of robust sampling design. We then illustrated the applications of these models with two case studies, one representing a competition system (mallard Anas platyrhynchos , northern pintail Anas acuta ) with binomial observations and the other representing a predator-prey system (bobcat Lynx rufus , wild turkey Meleagris gallopavo ) with Poisson observations. The results of the simulation studies showed that the models provide unbiased parameter estimates regardless of the ecological system, observation process, and sampling situation. Case studies further demonstrated the capabilities of these models in revealing important ecological processes. More specifically, the first case study revealed a negative effect of the superior competitor, Mallard, on the population growth of the inferior competitor, pintail as well as different movement patterns between these species, while the second case study reveal a top-down effect of bobcat abundance on wild turkey population growth and their differential habitat preferences. The models developed in this study could be used by themselves on count data or serve as population sub-models in integrated modeling frameworks to provide insights about metapopulation dynamics of interacting species in heterogeneous landscapes. The flexible structures of these models made them highly adaptive and relevant in population and community ecology.

Methods in Ecology and Evolution↗
USGS2016

Smokey comes of age: Unmanned aerial systems for fire management

During the past century, fire management has focused on techniques both to protect human communities from catastrophic wildfire and to maintain fire-dependent ecological systems. However, despite a large and increasing allocation of resources and personnel to achieve these goals, fire management objectives at regional to global scales are not being met. Current fire management techniques are clearly inadequate for the challenges faced by fire managers, and technological innovations are needed. Advances in unmanned aerial systems (UAS) technology provide opportunities for innovation in fire management and science. In many countries, fire management organizations are beginning to explore the potential of UAS for monitoring fires. We have taken the next step and developed a prototype that can precisely ignite fires as part of wildfire suppression tactics or prescribed fires (fire intentionally ignited within predetermined conditions to reduce hazardous fuels, improve habitat, or mitigate for large wildfires). We discuss the potential for these technologies to benefit fire management activities, while acknowledging the sizeable sociopolitical barriers that prevent their immediate broad application.

Frontiers in Ecology and the Environment↗
USGS1996

Spatial uncertainty analysis: Propagation of interpolation errors in spatially distributed models

In simulation modelling, it is desirable to quantify model uncertainties and provide not only point estimates for output variables but confidence intervals as well. Spatially distributed physical and ecological process models are becoming widely used, with runs being made over a grid of points that represent the landscape. This requires input values at each grid point, which often have to be interpolated from irregularly scattered measurement sites, e.g., weather stations. Interpolation introduces spatially varying errors which propagate through the model We extended established uncertainty analysis methods to a spatial domain for quantifying spatial patterns of input variable interpolation errors and how they propagate through a model to affect the uncertainty of the model output. We applied this to a model of potential evapotranspiration (PET) as a demonstration. We modelled PET for three time periods in 1990 as a function of temperature, humidity, and wind on a 10-km grid across the U.S. portion of the Columbia River Basin. Temperature, humidity, and wind speed were interpolated using kriging from 700- 1000 supporting data points. Kriging standard deviations (SD) were used to quantify the spatially varying interpolation uncertainties. For each of 5693 grid points, 100 Monte Carlo simulations were done, using the kriged values of temperature, humidity, and wind, plus random error terms determined by the kriging SDs and the correlations of interpolation errors among the three variables. For the spring season example, kriging SDs averaged 2.6??C for temperature, 8.7% for relative humidity, and 0.38 m s-1 for wind. The resultant PET estimates had coefficients of variation (CVs) ranging from 14% to 27% for the 10-km grid cells. Maps of PET means and CVs showed the spatial patterns of PET with a measure of its uncertainty due to interpolation of the input variables. This methodology should be applicable to a variety of spatially distributed models using interpolated inputs.

Ecological Modelling↗
USGS2020

Ratcheting up rigor in wildlife management decision making

The wildlife management institution has been transforming to ensure relevance and positive conservation outcomes into the future. Continuous improvement of decision making is one aspect of this transformation, but many obstacles hinder systematic approaches to decision making. One can point to examples of formal decision science applications by state and federal agencies in the United States, but generally decision making is not as methodical as the biological, ecological, or social sciences that inform wildlife policy and management decisions. We describe our observations — based on first-hand experiences — with decision making in wildlife management, present reasons why making decisions is difficult, identify challenges faced by wildlife managers at various levels of governance, and address measures wildlife managers can employ to overcome these challenges. We acknowledge that no panacea, simple recipe or one-size-fits-all prescription exists for wildlife management decision making. Nevertheless, we hope the combination of (a) describing how a systematic framework for decision making can benefit stakeholders, managers and conservation outcomes and (b) providing specific suggestions for such a framework will encourage agencies to continue taking steps to improve decision making processes.

Wildlife Society Bulletin↗
USGS2012

Use of alligator hole abundance and occupancy rate as indicators for restoration of a human-altered wetland

Use of indicator species as a measure of ecosystem conditions is an established science application in environmental management. Because of its role in shaping wetland systems, the American alligator (Alligator mississippiensis) is one of the ecological indicators for wetland restoration in south Florida, USA. We conducted landscape-level aerial surveys of alligator holes in two different habitats in a wetland where anthropogenic modification of surface hydrology has altered the natural system. Alligator holes were scarcer in an area where modified hydrology caused draining and frequent dry-downs compared to another area that maintains a functional wetland system. Lower abundance of alligator holes indicates lack of alligator activities, lower overall species diversity, and lack of dry-season aquatic refugia for other organisms. The occupancy rate of alligator holes was lower than the current restoration target for the Everglades, and was variable by size class with large size-class alligators predominantly occupying alligator holes. This may indicate unequal size-class distribution, different habitat selection by size classes, or possibly a lack of recruitment. Our study provides pre-restoration baseline information about one indicator species for the Everglades. Success of the restoration can be assessed via effective synthesis of information derived by collective research efforts on the entire suite of selected ecological indicators.

Florida↗
USGS2021

Assessing the uncertainties in climatic estimates based on vegetation assemblages: Examples from modern vegetation assemblages in the American Southwest

Assemblages of fossil plant remains have been widely used to reconstruct past climatic conditions, usually through the application of methods that involve either finding vegetation analogues on the modern landscape (and using the modern associated climatic values as the basis for an estimate) or using the modern climatic ranges of individual taxa in an assemblage to determine the range of a given climate variable that would allow these plant taxa to live together. Although these approaches are relatively straightforward, it is difficult to assess the uncertainties associated with each approach, particularly in regard to their application to plant macrofossil assemblages. To explore the uncertainty that may arise from inaccuracy and imprecision in climate reconstructions and from ecological considerations we used variants of both approaches to estimate climate from two data sets of modern vegetation assemblages from the southwestern United States: (1) 1752 gridded “virtual plant assemblages” based on plant range maps that provide uniform spatial coverage of the presence or absence of major woody plant taxa across the study area; and (2) 43 modern packrat ( Neotoma spp.) midden presence-absence assemblages that are similar to fossil midden assemblages. By comparing observed and estimated climate values, we evaluated the quality of the climate estimates, identified sources of uncertainty, and characterized the nature and magnitude of the effects of these uncertainties on the climate estimates. Uncertainties in estimating climate from vegetation assemblages arise because any given plant taxon (or assemblage) must have the resiliency to survive a range of climatic variability, and because of the strong intercorrelations among climatic variables in the modern climate data. Additional sources of uncertainty in climate estimates from plant assemblages include: (1) the modern climate and plant distribution data that are selected as the basis for estimation; (2) the particular quantitative approach that is used to estimate climate; (3) the sufficiency of the number of taxa in the analysis for providing an unbiased representation of the vegetation community as it existed for each time period in the analysis; and, (4) the location of the assemblage on the climatic and environmental gradients in the calibration data set for each climate variable under consideration. We conclude that vegetation assemblages can provide valid and reproducible estimates of climatic variables and that the primary trends and mapped patterns in the observed climate data can be reconstructed from such estimates. However, many factors may affect the quality of an estimate from a given plant assemblage, including aspects of data selection, data adequacy, methodologies, and the location of the assemblage site relative to gradients in the base climate data. It is particularly difficult to accurately estimate extreme values in the observed climate data, because estimated values from either end of an observed climate gradient necessarily “move toward the middle” of the gradient. In addition, the interval chosen to represent modern climate (here we used 1961 to 1990) may have a large impact on the size of the estimated difference between modern and past climate at a given site.

Arizona, California, Colorado, Nevada, New Mexico,↗
USGS2020

Estimating and forecasting spatial population dynamics of apex predators using transnational genetic monitoring

The ongoing recovery of terrestrial large carnivores in North America and Europe is accompanied by intense controversy. On the one hand, reestablishment of large carnivores entails a recovery of their most important ecological role, predation. On the other hand, societies are struggling to relearn how to live with apex predators that kill livestock, compete for game species, and occasionally injure or kill people. Those responsible for managing these species and mitigating conflict often lack fundamental information due to a long-standing challenge in ecology: How do we draw robust population-level inferences for elusive animals spread over immense areas? Here we showcase the application of an effective tool for spatially explicit tracking and forecasting of wildlife population dynamics at scales that are relevant to management and conservation. We analyzed the world’s largest dataset on carnivores comprising more than 35,000 noninvasively obtained DNA samples from over 6,000 individual brown bears ( Ursus arctos ), gray wolves ( Canis lupus ), and wolverines ( Gulo gulo ). Our analyses took into account that not all individuals are detected and, even if detected, their fates are not always known. We show unequivocal quantitative evidence of large carnivore recovery in northern Europe, juxtaposed with the finding that humans are the single-most important factor driving the dynamics of these apex predators. We present maps and forecasts of the spatiotemporal dynamics of large carnivore populations, transcending national boundaries and management regimes.

Proceedings of the National Academy of Sciences of↗
USGS2021

Nest microclimates of Greater Sage-Grouse in a post-megafire landscape: does selection equate to success?

Temperature at fine spatial scales is an important driver of nest site selection for many avian species during the breeding season and can influence nest success. Sagebrush ( Artemisia spp. ) communities have areas with high levels of vegetation heterogeneity and high thermal variation; however, fire removes vegetation that provides protection from predators and extreme environmental conditions. To examine the influence of microclimates on Greater Sage-Grouse ( Centrocercus urophasianus ) nest site selection and nest success in a fire affected landscape, we measured black bulb temperature (Tbb) and vegetation attributes (e.g. visual obstruction) at 3 spatial scales (i.e. nest bowl, microsite, and landscape) in unburned and burned areas. Nest bowls exhibited greater buffering of Tbb than both nearby microsites and the broader landscape. Notably, nest bowls were warmer in cold temperatures, and cooler in hot temperatures, than nearby microsites and the broader landscape, regardless of burn stage. Nest survival was higher for nests in unburned areas compared to nests in burned areas (unburned NS = 0.43, 95% CI: 0.33 to 0.54; burned NS = 0.24, 95% CI: 0.10 to 0.46). Amount of bare ground was negatively associated with nest survival, but effects diminished as the amount of bare ground reached very low levels. Shrub height and visual obstruction were positively associated with nest survival during the entire study period whereas, minimum Tbb had a weaker effect. Our findings demonstrate that thermoregulatory selection by Greater Sage-Grouse at nest sites had marginal effects on their nest survival. However, given that increases in vegetation structure (e.g. shrub height) provides thermal refuge and increases nest survival, vegetation remnants or regeneration in a post-fire landscape could be critical to Greater Sage-Grouse nesting ecology.

Oregon, Nevada↗
USGS2020

Using value of information to prioritize research needs for migratory bird management under climate change: A case study using federal land acquisition in the United States

In response to global habitat loss, many governmental and non‐governmental organizations have implemented land acquisition programs to protect critical habitats permanently for priority species. The ability of these protected areas to meet future management objectives may be compromised if the effects of climate change are not considered in acquisition decisions. Unfortunately, the effects of climate change on ecological systems are complex and plagued by uncertainty, making it difficult for organizations to prioritize research needs to improve decision‐making. Herein, we demonstrate the use of qualitative value of information analysis to identify and prioritize which sources of uncertainty should be reduced to improve land acquisition decisions to protect migratory birds in the face of climate change. The qualitative value of information analysis process involves four steps: ( i ) articulating alternative hypotheses; ( ii ) determining the magnitude of uncertainty regarding each hypothesis; ( iii ) evaluating the relevance of each hypothesis to acquisition decision‐making; and ( iv ) assessing the feasibility of reducing the uncertainty surrounding each hypothesis through research and monitoring. We demonstrate this approach using the objectives of 3 U.S. federal land acquisition programs that focus on migratory bird management. We used a comprehensive literature review, expert elicitation, and professional judgement to evaluate 11 hypotheses about the effect of climate change on migratory birds. Based on our results, we provide a list of priorities for future research and monitoring to reduce uncertainty and improve land acquisition decisions for the programs considered in our case study. Reducing uncertainty about how climate change will influence the spatial distribution of priority species and biotic homogenization were identified as the highest priorities for future research due to both the value of this information for improving land acquisition decisions and the feasibility of reducing uncertainty through research and monitoring. Research on how changes in precipitation patterns and winter severity will influence migratory bird abundance is also expected to benefit land acquisition decisions. By contrast, hypotheses about phenology and migration distance were identified as low priorities for research. By providing a rigorous and transparent approach to prioritizing research, we demonstrate that qualitative value of information is a valuable tool for prioritizing research and improving management decisions in other complex, high‐uncertainty cases where traditional quantitative value of information analysis is not possible. Given the inherent complexity of ecological systems under climate change, and the difficulty of identifying management‐relevant research priorities, we expect this approach to have wide applications within the field of natural resource management.

Biological Reviews↗
USGS2006

Isolation and characterization of microsatellite loci in Alasmidonta heterodon (Bivalvia: Unionidae)

We developed 13 species-specific microsatellite markers for the federally endangered Atlantic slope unionid Alasmidonta heterodon. Four to 18 alleles per locus were observed among 30 individuals. Observed heterozygosity throughout the loci ranged from 26.9 to 86.2% and averaged 63.6%. Estimates of individual pairwise genetic distances indicated that levels of genetic diversity among loci were sufficient to produce unique multilocus genotypes for all animals surveyed. Randomization tests showed that genotypes for this collection were consistent with Hardy-Weinberg expectations, and no significant linkage disequilibrium was observed between loci. These loci therefore appear suitable for population surveys, kinship assessment and other such applications. ?? 2006 Blackwell Publishing Ltd.

Molecular Ecology Notes↗
USGS2008

Application of the new keystone-species concept to prairie dogs: How well does it work?

It has been suggested that the keystone-species concept should be dropped from ecology and conservation, primarily because the concept is poorly defined. This prompted Power et al. (1996) to refine the definition: keystone species have large effects on community structure or ecosystem function (i.e., high overall importance), and this effect should be large relative to abundance (i.e., high community importance). Using prairie dogs ( Cynomys spp.) as an example, I review operational and conceptual difficulties encountered in applying this definition. As applied to prairie dogs, the implicit assumption that overall importance is a linear function of abundance is invalid. In addition, community importance is sensitive to abundance levels, the definition of community, and sampling scale. These problems arise largely from the equation for community importance, as used in conjunction with removal experiments at single abundance levels. I suggest that we shift from the current emphasis on the dualism between keystone and nonkeystone species and instead examine how overall and community importance vary (1) with abundance, (2) across spatial and temporal scales, and (3) under diverse ecological conditions. In addition, I propose that a third criterion be incorporated into the definition: keystone species perform roles not performed by other species or processes. Examination of how these factors vary among populations of keystone species should help identify the factors contributing to, or limiting, keystone-level functions, thereby increasing the usefulness of the keystone-species concept in ecology and conservation. Although the quantitative framework of Power et al. falls short of being fully operational, my conceptual guidelines may improve the usefulness of the keystone-species concept. Careful attention to the factors that limit keystone function will help avoid misplaced emphasis on keystone species at the expense of other species.

Conservation Biology↗